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Wang, and J.-T. Teng in their paper develop and compare the seller's profit per unit time under each of three payment methods - advance, cash, and credit. In their paper, S. Sarkar, S. Tiwari, and B. C. Giri present a continuous-review vendor-buyer supply chain (SC) model and uncovers the best policy that minimizes the system's total expected cost. The authors investigate the contracts that the manufacturer offers to the retailers and finds the optimal pricing and ordering decisions made by retailers and the best contract that includes maximum profit for the supply chain. The analysis of large-scale data generated by humans, online activity in different web and social platforms is a challenging problem faced by researchers, practitioners, and academicians. [Extracted from the article]

In today's competitive environment, industries are required to increase reliability and safety level of their equipment with reasonable cost. Consequently, it is essential to select the appropriate maintenance strategy. In the paper industry, pumping of cooked pulp requires abrasion- and sometimes corrosion-resistant pumps that are able to handle up to 70 % solids content. But the maintenance engineer and supervisor often face failures of the pump. Hence, this article describes the application of multi criteria decision-making (MCDM) technique for the selection of optimum maintenance strategy for pumps used in the paper industry. The proposed hybrid MCDM model comprises fuzzy analytical hierarchy process (FAHP), grey relational analysis (GRA), and technique for order preference by similarity to ideal solution (TOPSIS) technique. The FAHP is used to compute the criteria weights whereas GRA-TOPSIS is used for determining the ranking of alternatives. This study discusses four maintenance strategies: corrective maintenance, predictive maintenance, time-based preventive maintenance, and condition-based maintenance. Four main criteria-safety, cost, added value, and feasibility-have been used to evaluate the optimum maintenance strategy. [ABSTRACT FROM AUTHOR]

The 2017 International Conference on Multiple Objective Programming and Goal Programming (MOPGP 2017) has been organized to disseminate recent theoretical and methodological developments, significant technical applications, case studies and survey results in the related area. Multiple Objective Programming (MOP), also known in literature as multi-objective optimization, vector optimization, multicriteria optimization, multiattribute optimization or Pareto optimization, is a subarea of Multiple Criteria Decision Making (MCDM) or Multiple Criteria Decision Analysis (MCDA) and it is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. If we suppose that HT ht is ordered by the classical Pareto cone HT ht , then HT ht if HT ht . [Extracted from the article]

Over the last few decades, researches related to the impact of production and industrial manufacturing on environmental sustainability, coupled with multi-dimensional multi-criteria decision analysis and performance evaluation has consistently gained importance. However, no significant work in which an effort to optimize the total production process with the consideration of the positive and negative impacts of each input and output on Environmental sustainability has been noticed. The main aim of our paper is to address this gap. In this paper, an effort has been made to develop a realistic optimization model wherein a manufacturing firm has been considered to function with several decision-making units taking into account the effects of factors like profit, employment generation, social development, environmental pollution and sustainability. The various inputs employed and outputs produced by the firm are responsible for having negative impacts on the environment, besides creative value generation. With due consideration to both these values instead of mere profit, the model determines and explores the firm's decision considering different objectives. The optimization problem has been solved by a GA developed by us and demonstrated with numerical examples. The solutions of the numerical examples point towards some interesting revelations and indicate some prospective future research directions which contributes to this field of research. [ABSTRACT FROM AUTHOR]

The objective of this paper is to propose a novel dual-level multisource information fusion approach for handling open multicriteria decision-making (MCDM) issues related to accurately determining the weights of criteria while considering the relative importance of expert opinions, handling heterogeneous information, and selecting an appropriate MCDM ranking method. The proposed approach includes two levels. The first integrates the "analytic hierarchy process (AHP)—full consistency method (FUCOM)", which comprises two phases. In the first phase, criteria weights are assigned using AHP, and FUCOM is employed to correct inconsistencies. In the second phase, the weights are computed for decision-makers. Triangular fuzzy numbers are employed due to their ability to encapsulate all the utilized heterogeneous data types. At the second level of the approach, three well-known distance-based methods, including "technique for order preference by similarity to ideal solution", "visekriterijumska optimizacija i kompromisno resenje", and "multiattributive border approximation area comparison", are fused to process a homogeneous decision matrix and provide comprehensive and robust rankings for alternatives. To develop our novel approach, a renewable energy source for Pakistan's electricity generation is adopted as a case study. The decision matrix contains four alternatives (i.e., hydropower, biomass energy, solar energy, and wind energy) and six main evaluation criteria (i.e., economic, quality of energy, social, political, environmental, and technical), with several subevaluation criteria under each criterion. The findings of the proposed approach were as follows: A2 was in the first rank with a score of 1.7889, and A4 was in the last rank with a score of 0.1199. The rest of the alternatives were distributed between them. The paper's implications include the advancement of decision-making methods, enhancement of decision-making outcomes, and addressing heterogeneous information to highlight the relative importance of experts. [ABSTRACT FROM AUTHOR]

Purchasing occupies a strategic role in supply chain management for a firm and is the driver of competitive advantage. Owing to the high purchase cost to revenue ratio, decisions such as evaluation, selection, and performance management of suppliers are of the matter of immense interest to firms. Multi-criteria decision making tools allow the purchasing managers to evaluate the suppliers holistically. One such tool, data envelopment analysis (DEA) has been used extensively for supplier evaluation and selection. This paper presents a comprehensive review of 161 articles published since 2000, on the application of DEA in supplier selection. These articles are located from the Scopus database. With little existing literature on a full-fledged review, this work envisages to be first of its kind, by aiding DEA practitioners in purchasing function. The analysis of the study indicates the emergence of the theme of green supply chain and sustainability in recent years as well as the adoption of hybrid approaches to solving the problem of supplier selection using DEA. The paper presents various classifications of DEA methods based on input criteria, sectors of application, and industry-wide case studies, which can be used as a quick reckoner by an academician or a purchasing manager. [ABSTRACT FROM AUTHOR]

The dynamic multiple-criteria decision-making (MCDM) approach has drawn immense attention in the decision analysis domain over recent years. An essential problem of this dynamic process is how to retrieve the utmost from historical data. Although most previous dynamic MCDM studies process historical data only with external representatives, namely scores given to alternatives on each criterion, we argue that internal patterns of historical data are also essential to achieve a more comprehensive evaluation of alternatives. Nevertheless, a data-driven methodology aiming to capture internal patterns of historical data and consequently provide decision-makers with meaningful insights is still lacking. In this paper, we propose a framework that serves as integration within which both external representations and internal patterns are used to make a more comprehensive evaluation. Then we apply our framework to student evaluations and country-level risk assessments in the contexts of additive and fuzzy measures, respectively. Both cases show that either using external representatives or internal patterns alone leads to entirely different and even biased results. On the contrary, integrating external representations and internal patterns can offer more flexibility and higher interpretation power. [ABSTRACT FROM AUTHOR]

The importance of determining the appropriate location for the construction of the main centers of a company is quite tangible, so much so that the senior managers of an organization are trying to find the appropriate decision-making methods in this regard. In discrete decision-making methods, we see the existence of a decision-making matrix containing information on different options compared to the problem evaluation criteria. In this paper, a new decision-making method is presented in a way that tries to evaluate options more accurately by considering the possibility of changing the criteria's desirability in different ranges. It is not always appropriate to increase\decrease a positive\negative criterion. Even in some situations, crossing a certain limit can reduce the desirability of the desired criterion. Therefore, we will introduce the concept of value alteration boundaries for evaluation criteria in the formation of a decision matrix, which tries to examine the decision problems more realistically. Also, in the examination of alternatives, with simultaneous attention to ideal, anti-ideal and average solutions, evaluation and ranking based on accumulation and skewness of alternatives are presented. The present paper has examined the validation of methods by examining several numerical examples and also evaluating the candidate locations for the construction of a central warehouse in Gohar Zamin Mining and Industrial Company. Also, sensitivity analysis includes checking with other existing multi-criteria decision-making methods, changes in the number of problem options and checking the stability of the method, changes in the weight of the criteria and changes in the value alteration boundaries. Analysis of results shows that the proposed methods are efficient and suitable for dealing with multi-criteria decision-making problems. [ABSTRACT FROM AUTHOR]

This paper describes a generalized Diophantine fuzzy sets, which can be seen as a generalization of both Diophantine fuzzy sets and Pythagorean fuzzy sets. We define the basic properties of generalized Diophantine fuzzy set, as well as their relationships and distances. We compare Diophantine fuzzy sets with other Diophantine Pythagorean fuzzy sets to demonstrate their importance in the literature. We introduce new operators including necessity, possibility, accuracy function and score function. Furthermore, we discuss the new distance between normalized Euclidean distance and normalized Hamming distance. For a generalized Diophantine fuzzy relation, image and inverse image functions are defined. Numerous real-world applications can be found for the prevalent ideas of intuitionistic fuzzy sets, Pythagorean fuzzy sets, Diophantine fuzzy sets and q-rung orthopair fuzzy sets. Regretfully, these theories about the membership and non-membership grades have their own limits. We provide a new idea the generalized Diophantine fuzzy set that eliminates these limitations by including reference parameters. Compared to other kinds of fuzzy sets, there are more applications for generalized Diophantine fuzzy sets. We offer practical examples that show how different enhanced distances might be used in everyday situations. Additionally, to demonstrate the effectiveness of the suggested approach, flowchart based multi-criteria decision-making is provided and used to a numerical example. The outcomes are assessed for various parameter values. Furthermore, a comparative analysis developed to demonstrate the superiority of the suggested technique over current methodologies. [ABSTRACT FROM AUTHOR]

In most project portfolio selection (PPS) situations, the presence of multiple attributes and decision-maker preference is inevitable. As Multi-criteria Decision Analysis (MCDA) methods provide a framework well-suited to deal with these challenges in PPS problems, the use of MCDA methods in real-life PPS problems has increased in recent years. This paper provides a comprehensive literature review of the use of different MCDA methods and their individual or combined utilization with other modeling techniques to support PPS problems. First, we summarize how MCDA methods are used in different modeling approaches. Second, we examine the mathematical models that are generally used to combine MCDA with mathematical programming techniques to solve PPS problems with resource constraints. Third, we present the drawbacks of combined utilization and discuss recent advances. Finally, we visualize the summary of the reviewed papers as a decision tree to assist researchers and practitioners in the use of MCDA methods in a specific PPS context and propose some future research directions. [ABSTRACT FROM AUTHOR]

Since at the two conferences many presentations addressed a variety of different multiobjective optimisation problems, we decided to focus this special issue distinctively on recent developments in multiobjective optimisation falling within the a posteriori paradigm of multiple criteria decision making (MCDM). We observe that multiobjective optimisation under uncertainty and multiobjective optimisation in practical applications are the dominating research themes throughout this volume because a majority of studies address either one or both of them simultaneously. The type of optimisation problems addressed ranges from scheduling problems with two objectives to mixed integer linear optimisation problems and nonlinear optimization problems, both with only continuous and with continuous as well as binary variables. [Extracted from the article]

The rough set (RS) and multi-granulation rough set (MGRS) theories have been successfully extended to accommodate preference analysis by substituting the equivalence relation (ER) with the dominance relation (DR). On the other hand, bipolarity refers to the explicit handling of positive and negative aspects of data. In this paper, with the help of bipolar fuzzy preference relation (BFPR) and bipolar fuzzy preference δ -covering (BFP δ C), we put forward the idea of BFP δ C based optimistic multi-granulation bipolar fuzzy rough set (BFP δ C-OMG-BFRS) model and BFP δ C based pessimistic multi-granulation bipolar fuzzy rough set (BFP δ C-PMG-BFRS) model. We examine several significant structural properties of BFP δ C-OMG-BFRS and BFP δ C-PMG-BFRS models in detail. Moreover, we discuss the relationship between BFP δ C-OMG-BFRS and BFP δ C-PMG-BFRS models. Eventually, we apply the BFP δ C-OMG-BFRS model for solving multi-criteria decision-making (MCDM). Furthermore, we demonstrate the effectiveness and feasibility of our designed approach by solving a numerical example. We further conduct a detailed comparison with certain existing methods. Last but not least, theoretical studies and practical examples reveals that our suggested approach dramatically enriches the MGRS theory and offers a novel strategy for knowledge discovery, which is practical in real-world circumstances. [ABSTRACT FROM AUTHOR]

When an emergency occurs, effective decisions should be made in a limited time to reduce the casualties and economic losses as much as possible. In the past decades, emergency decision-making (EDM) has become a research hotspot and a lot of studies have been conducted for better managing emergency events under tight time constraint. However, there is a lack of a comprehensive bibliometric analysis of the literature on this topic. The objective of this paper is to provide academic community with a complete bibliometric analysis of the EDM researches to generate a global picture of developments, focus areas, and trends in the field. A total of 303 journal publications published between 2010 and 2020 were identified and analyzed using the VOSviewer in regard to cooperation network, co-citation network, and keyword co-occurrence network. The findings indicate that the annual publications in this research field have increased rapidly since 2014. Based on the cooperation network and co-citation network analyses, the most productive and influential countries, institutions, researchers, and their cooperation networks were identified. Using the co-citation network analysis, the landmark articles and the core journals in the EDM area are found out. With the help of the keyword co-occurrence network analysis, research hotspots and development of the EDM domain are determined. According to current trends and blind spots in the literature, possible directions for further investigation are finally suggested for EDM. The literature review results provide valuable information and new insights for both scholars and practitioners to grasp the current situation, hotspots and future research agenda of the EDM field. [ABSTRACT FROM AUTHOR]

Researchers have addressed uncertainty in multicriteria decision making from the perspective of the performance values of the alternatives, weighting of the evaluation criteria, and the evaluation methods. Still, they are yet to address the uncertainty caused by the normalization approach. In this paper, we show that different normalization methods, namely sum normalization, min–max normalization, vector normalization, and maximization normalization, can result in different rankings of the alternatives while the performance values and weights are unchanged. We applied the grey system theory to address the problem of uncertainty in this study from three aspects: alternative performance values measurement, criteria weighting, and decision matrix/table normalization within a period. The grey hybrid normalization method is proposed as the main contribution in this paper. Then, we present the rankings of 48 cities under uncertainty to decide the location of a branch office of a Chinese electric vehicle manufacturer as a practical example based on the grey entropy weighting method and grey relational analysis with positive and negative references (GRA-PNR) within the period from the year 2019 to 2021. The research results using this approach ranked New York City the best, with a stock market capitalization of economy validity as the top contributor in terms of weighting. Finally, we used simple additive weighting with grey value and the technique for order of preference by similarity to ideal solution with grey value methods to validate the study results. [ABSTRACT FROM AUTHOR]

Stochastic multicriteria acceptability analysis (SMAA) is a family of multiple criteria decision making (MCDM) methods dealing with incomplete, imprecise, and uncertain information on the evaluations and preference model parameters. As it provides a general framework that has extensions to deal with various specificities in MCDM problems, the development of SMAA methods and their applications in real-life decision-making problems have been increased over the recent years. This paper provides an up-to-date literature review of different SMAA methods and their applications in various areas. First, we selected, from different on-line data base, 118 articles published between 1998 and 2017. We categorized the selected papers into theoretical and applied. While the theoretical papers were analyzed based on the method's aggregation procedure, type of problem, type of method's outputs and inputs, the applied papers were separated and analyzed by application areas. Then, we provide some descriptive statistics, analyzing the papers regarding to publication year and journals of publication. Finally, we provide some guidelines to assist decision-makers in the choice of a SMAA method on a specific decision-making context and some future research directions. [ABSTRACT FROM AUTHOR]

Egypt's urban communities face many threats, including, pluvial floods, heat waves, and lack of publicly accessible urban green spaces. Nature-based solutions such as constructed wetlands (CWs) present a promising solution that could offer a wide range of ecosystem services (ES). However, the adoption of CWs is challenged by the lack of local planning guides and uncertainty about potential benefits. There are various models and tools available for quantifying and valuing ES, however, many of them are either highly complex or require extensive data and expertise. The aim of this paper is to develop a GIS-based multi-criteria decision model to select CW sites based on the supply and demand of ES. The model is to operate on three main stages: (i) demand: based on the need for risk reduction or benefit provisioning, (ii) potential sites (PSs): identify and score suitable sites for establishing a CW, and (iii) supply: define the service benefiting areas (SBA). An experimental approach is used, where the model is tested on New Damietta, an Egyptian Mediterranean city, proving the model is a reliable decision-making tool during preliminary urban planning stages due to its practicality, flexibility, and reasonable data requirements. [ABSTRACT FROM AUTHOR]

Objective: To provide a comprehensive framework for value assessment of artificial intelligence (AI) in radiology. Methods: This paper presents the RADAR framework, which has been adapted from Fryback and Thornbury's imaging efficacy framework to facilitate the valuation of radiology AI from conception to local implementation. Local efficacy has been newly introduced to underscore the importance of appraising an AI technology within its local environment. Furthermore, the RADAR framework is illustrated through a myriad of study designs that help assess value. Results: RADAR presents a seven-level hierarchy, providing radiologists, researchers, and policymakers with a structured approach to the comprehensive assessment of value in radiology AI. RADAR is designed to be dynamic and meet the different valuation needs throughout the AI's lifecycle. Initial phases like technical and diagnostic efficacy (RADAR-1 and RADAR-2) are assessed pre-clinical deployment via in silico clinical trials and cross-sectional studies. Subsequent stages, spanning from diagnostic thinking to patient outcome efficacy (RADAR-3 to RADAR-5), require clinical integration and are explored via randomized controlled trials and cohort studies. Cost-effectiveness efficacy (RADAR-6) takes a societal perspective on financial feasibility, addressed via health-economic evaluations. The final level, RADAR-7, determines how prior valuations translate locally, evaluated through budget impact analysis, multi-criteria decision analyses, and prospective monitoring. Conclusion: The RADAR framework offers a comprehensive framework for valuing radiology AI. Its layered, hierarchical structure, combined with a focus on local relevance, aligns RADAR seamlessly with the principles of value-based radiology. Critical relevance statement: The RADAR framework advances artificial intelligence in radiology by delineating a much-needed framework for comprehensive valuation. Keypoints: • Radiology artificial intelligence lacks a comprehensive approach to value assessment. • The RADAR framework provides a dynamic, hierarchical method for thorough valuation of radiology AI. • RADAR advances clinical radiology by bridging the artificial intelligence implementation gap. [ABSTRACT FROM AUTHOR]

The aim of this paper is to solve an agricultural technology packages selection problem by considering multiple dimensions which influence a maize producer's preferences. The decision-making process is aided by a new multicriteria method for eliciting scale constants in additive models: flexible and interactive tradeoff (FITradeoff). This method works with partial information, obtained from the decision maker (DM), and thus reduces the time that the DM has to spend on the process for eliciting his/her preferences as he/she may avoid answering difficult questions. The decision-making process makes use of a decision support system (DSS), in which the DM interactively gives preference statements in a structured manner. The DSS gives flexibility to the DM, in such way that he/she gives as much information as he/she is willing to. Graphical visualization is provided at each step in order to help the DM's analyses. Throughout the description of an application, some insights are provided including a discussion of the advantages and features of the FITradeoff method. [ABSTRACT FROM AUTHOR]

Analytical Hierarchy Process (AHP) has evolved since its inception and has contributed mainly to multi-criteria decision-making (MCDM) to solve complex problems. It is a widespread technique that uses group decision-making approach to solve problems in business operations, mathematics, and numerous other scientific fields. While its applications are numerous, a handful of researchers have studied the growth trajectory of AHP. Whilst these seminal works have discussed the evolution of AHP in different contexts and using contemporary techniques, we complement them by presenting and reflecting on the unchartered and pressing need of charting the managerial and theoretical evolution of AHP, over the last decade. We do this through a systematic and thematic review of the extant literature. This study uses the Scopus database to extract papers published between 2012 and 2021 in decision science with an overlap with operations research and information systems. The study follows Tranfield et al. (2003)'s guidelines to understand the past trends of AHP along three key dimensions and offers future directions. The study also showcases key trends using historiography and uses data visualization techniques to understand the use of AHP with other MCDM techniques. [ABSTRACT FROM AUTHOR]

A large number of materials and various criteria fashion material selection problems as complex multi-criteria decision-making (MCDM) problems. This paper proposes a new decision-making method called the simple ranking process (SRP) to solve complex material selection problems. The accuracy of the criteria weights has a direct impact on the outcomes of the new method. In contrast to current MCDM methods, the normalization step has been eliminated from the SRP method as a potential source of producing incorrect results. The application of the method is appropriate for situations with high levels of complexity in material selection because it only considers the ranks of alternatives in each criterion. The first scenario of vital-immaterial mediocre method (VIMM) is used as a tool to derive criteria weights based on expert assessment. The result of SRP is compared with a number of MCDM methods. In order to evaluate the findings of analytical comparison, a novel statistical measure known as compromise decision index (CDI) is proposed in this paper. CDI revealed that the MCDM methods' outputs for solving the material selection could not be theoretically proven and requires to be evaluated through practice. As a result, the dependency analysis-an additional innovative statistical measure is introduced to demonstrate the reliability of MCDM methods by assessing its dependency on criteria weights. The findings demonstrated that SRP is extremely reliant on criteria weights and its reliability rises with the number of criteria, making it a perfect tool for solving challenging MCDM problems. [ABSTRACT FROM AUTHOR]

Megacities around the world are highly concerned about the impacts of urban transportation. The rapid urbanization and motorization in megacities have a direct impact on sustainable development. Hence, it is very frequently to find the multiple actors from both private and public sectors involved in the design and operation of urban passenger transportation systems to make decisions that seek at optimizing their own particular objectives. However, urban passenger transport system is a very complex task involving multiple criteria related to economic, environmental and socio-political issues. Multi-criteria decision-making (MCDM) techniques actually aid the decision making process by assessing such problems. This paper presents a review of research papers published between 1982 and 2014 (up to May) concerning MCDM for the design and operation of urban passenger transport systems. From the analysis over more than 30 years, the current paper highlights the importance of taking into account the multiplicity of actors and their own decision criteria, as well as the resolution technique. Finally, some suggestions for future research are discussed. [ABSTRACT FROM AUTHOR]

A smart grid integrates communication networks with the conventional electrical grid. Due to their potential, smart grids are anticipated to achieve widespread deployment. A key component of the success and adoption of smart grids is reliability. Without knowing users' impressions of the reliability of the smart grid, users will not easily accept and participate in it or its services. However, very few studies address smart grid reliability from the perspective of users. Thus, there is a urgent need to identify key factors that affect smart grid reliability from the user's viewpoint. The goal of this paper is to examine user perceptions of smart grid reliability and assess their success factors in an effort to close the gap in the literature. This paper propose a model to investigate and determine the most crucial factors that affect the smart grid's reliability based on the Multiple-criteria decision-making (MCDM) method. Firstly, a comprehensive literature analysis was conducted to determine the criteria and sub-criteria used to construct the model; then, the model is constructed using fifteen sub-criteria covering big data, network systems, and grid efficiency criteria; finally, the Fuzzy Analytic Hierarchy Approach (FAHP) and fuzzy triangular numbers are used to evaluate and prioritize the criteria. Twenty smart grid experts were consulted to collect data. The results indicate the significance of the 'Big Data' criterion, closely followed by 'Grid Efficiency' criterion. Additionally, it is discovered that the sub-criteria of 'Privacy' and 'Interoperability' had a significant impact on the reliability of the smart grid. The sensitivity analysis shows the variation of factors ranking and the stability and robustness of the model and the results. The research presented in this study has practical applications for academics, engineers, decision-makers, and stakeholders. [ABSTRACT FROM AUTHOR]

The goal of city logistics (CL) is to reconcile the interests of all stakeholders and find compromise solutions for problems associated with the urban logistics flows. A great number of CL initiatives have been the subject of research, analysis and practical application. Some of them indicated significant positive effects, but their implementation brought only partial effects. The non-systematic approach in problem-solving and neglect of other stakeholders' interests by the local government caused the failure of many applied CL initiatives. The purpose of this paper is to evaluate the CL initiatives categories sustainability, taking into consideration the goals of all stakeholder groups. This is the first paper analyzing various CL initiatives categories simultaneously, from the aspect of providers, shippers/receivers, local authorities, and residents, which is the main contribution of the paper. Twelve basic CL initiative categories were considered, while their assessment and ranking were performed with a novel hybrid multi-criteria decision-making (MCDM) model based on fuzzy Analytic Hierarchy Process and fuzzy Measurement Alternatives and Ranking according to Compromise Solution, which is another contribution of the paper. The results indicate that the development and implementation of logistics centers emerge as the best CL initiative category for solving CL problems in the city of Belgrade. The theoretical implications of this article are the creation of a framework for the evaluation of the sustainability of CL initiatives, as well as the novel MCDM model that could be used for problem-solving in different areas. The practical implication of the article is the provision of a framework for decision-makers, policy-creators and practitioners for supporting the process of plans development and initiative implementation in the field of CL. [ABSTRACT FROM AUTHOR]

A country that relies on developing industrialization and GDP requires a lot of energy. Biomass is emerging as one of the possible renewable energy resources that may be used to generate energy. Through the proper channels, such as chemical, biochemical, and thermochemical processes, it can be turned into electricity. In the context of India, the potential sources of biomass can be broken down into agricultural waste, tanning waste, sewage, vegetable waste, food, meat waste, and liquor waste. Each form of biomass energy so extracted has advantages and downsides, so determining which one is best is crucial to reaping the most benefits. The selection of biomass conversion methods is especially significant since it requires a careful study of multiple factors, which can be aided by fuzzy multi-criteria decision-making (MCDM) models. This paper proposes the normal wiggly interval-valued hesitant fuzzy-based decision-making trial and evaluation laboratory model (DEMATEL) and the Preference Ranking Organization METHod for Enrichment of Evaluations II (PROMETHEE) for assessing the problem of determining a workable biomass production technique. The proposed framework is used to assess the production processes under consideration based on parameters such as fuel cost, technical cost, environmental safety, and C O 2 emission levels. Bioethanol has been developed as a viable industrial option due to its low carbon footprint and environmental viability. Furthermore, the superiority of the suggested model is demonstrated by comparing the results to other current methodologies. According to comparative study, the suggested framework might be developed to handle complex scenarios with many variables. [ABSTRACT FROM AUTHOR]

This article elaborates on the connection between multiple criteria decision aiding (MCDA) and preference learning (PL), two research fields with different roots and developed in different communities. It complements the first part of the paper, in which we started with a review of MCDA. In this part, a similar review will be given for PL, followed by a systematic comparison of both methodologies, as well as an overview of existing work on combining PL and MCDA. Our main goal is to stimulate further research at the junction of these two methodologies. [ABSTRACT FROM AUTHOR]

The selection of transshipment and handling machinery in container terminals is a complex and responsible task due to a number of daily operations required. Accordingly, there is a need to manage a circular economy that integrates economic parameters and attitudes toward the environment. Depending on the size of the container terminal itself, a necessary set of means for performing transshipment and handling operations is designed. In this paper, based on the previously identified needs of the IRT Belgrade container terminal, the evaluation and selection of a reach stacker within large-scale group decision making under fuzzy environment was performed. The main goal of the paper is to create an adequate fuzzy group multi-criteria decision making (MCDM) model based on the integration of Fuzzy FUCOM (Full Consistency Method), Fuzzy MARCOS (Measurement of alternatives and ranking according to COmpromise solution) and Fuzzy Bonferroni Mean (BM) operator. It was formed a total of 15 criteria divided into three basic groups: economic, technological and technical, which were evaluated on the basis of 18 experts. To determine the weight values ​​of the criteria, the Fuzzy FUCOM method was applied through a total of 72 models averaged using the Fuzzy BM operator. Evaluation and selection of a reach stacker (RS) was performed using the Fuzzy MARCOS method and the Fuzzy BM operator. The obtained results have shown that the most important group of criteria in group decision making and processing of a larger set of data is the technological group. The best option is the seventh variant, and thus the requirement to select RS for the container terminal is met. The verification of the obtained results was performed through the following phases: the influence of the reverse rank fuzzy matrix, simulation of the weight values ​​of the criteria through 50 formed scenarios and comparison with two other MCDM methods in a fuzzy form. [ABSTRACT FROM AUTHOR]

Manufacturing resources allocation (MRA) is important area, and a significant challenge is encountered when considering high value, customized, complex structure and long lifespan of complex product system (CoPS). The relationship between uncertainty factors (i.e., inputs and outputs) of processes in CoPS's manufacturing, operation and maintenance needs comprehensive trade-offs in the preliminary MRA stage. Meanwhile, the CoPS's MRA schemes are contradictory from a customer's perspective with different emphasis on operating cost related to operation and maintenance stage. These problems are unavailable in traditional expressions for model and objective function. In this paper, a new variant of MRA multi-criteria decision-making (MCDM) model of CoPS (MRA&CoPS) is developed to evaluate MRA schemes with considering CoPS's lifecycle. Meanwhile, considering characteristics of CoPS and customer-involved MRA process, the three-layer criteria cumulative model is established. In the proposed method, intuitionistic fuzzy sets (IFSs) based subjective–objective hybrid fuzzy method is presented to deal with uncertainty of evaluation criteria. The weights of criteria are determined by the proposed intuitionistic fuzzy information entropy (IFIE). The hybrid IFIE-TOPSIS method is proposed to obtain the optimum MRA scheme by ranking results. An example of CoPS's MRA in a case enterprise is addressed to verify the rationality and validity of the proposed method. The results show that the proposed method is more preferable and robust in MCDM problem of MRA&CoPS. [ABSTRACT FROM AUTHOR]

Reliability allocation is a critical process to ensure the reliability of numerical control (NC) machines during the design phase. However, there are a few issues with the reliability allocation techniques that are currently in use. First, the reliability allocation of NC machine tools still along the lines of "System-Component-Part," which is difficult to apply to the motion characteristics of machine tools and guide the product design effectively. Second, the consistency and objectivity of the reliability allocation technique based on multicriteria decision-making (MCDM) are inadequate due to the reliance on expert knowledge. Third, the reliability allocation criteria and reliability benefit are not taken into account by the allocation approach based multi-objective optimization (MOO), which leads to conservative allocation results. Therefore, this paper proposes a hybrid reliability allocation method based on meta-action for NC machine tools that integrates meta-action theory, MCDM, and MOO. In addition, the "conservative allocation" problem in the allocation process is addressed using the reliability benefit function. Finally, the rationality, effectiveness, and applicability of the proposed method are verified with the hobbing machine as an example through discussion and comparison. [ABSTRACT FROM AUTHOR]

With the development of social and economic research, the judgements that people deal with are full of fuzziness and vagueness. It is convenient to use the linguistic q-rung orthopair fuzzy numbers to offer the qualitative uncertain information. Consequently, in this paper, we mainly study linguistic q-rung orthopair fuzzy preference relations (Lq-ROFPRs) and apply them to a multi-criteria decision-making (MCDM) problem. The multiplicative consistency of Lq-ROFPRs is first introduced, then a consistency-based model is established to derive the normalized linguistic q-rung orthopair fuzzy priority weight vector. The concept of acceptably multiplicative consistency is further defined, and an optimization model is formulated to repair the unacceptably multiplicative consistent Lq-ROFPR. To cope with the incomplete Lq-ROFPR, another programming model is built to ascertain the missing values. The weights of criteria are determined by constructing a possibility degree matrix. Subsequently, an MCDM problem with incomplete Lq-ROFPRs is considered and a step-by-step algorithm is put forward. Finally, the proposed method is applied to three examples, and the advantages of this new approach are also demonstrated. [ABSTRACT FROM AUTHOR]

City sustainability means a balance among economy, society, and environment in the rapid urbanization process. Effective assessment of city sustainability could guide a city to develop in the desired direction. Northeastern China was one of the forefronts of China's reform and opening up, but now it has become a "sore point" in national development. Liaoning province plays a crucial role in the process of realizing the revitalization of Northeastern China. This paper investigated the sustainability performances of cities in Liaoning by following the process of multi-criteria decision making. A novel weighting method was proposed based on Synergetics that considers the interrelationship among sustainability criteria. The results showed that the sustainability level of Liaoning was not ideal, with only two cities having sustainability performances over 0.55. The cities located in the Middle region had a higher sustainability level than those in the West and East regions. Moreover, the performances on the three dimensions were uncoordinated. The salary of employed staff and disposal income were the two important factors on sustainable development. The forecasting analysis showed that the sustainability level of the cities will develop at a rapid pace in the future. Finally, we put forward targeted suggestions for sustainable development in Liaoning province. [ABSTRACT FROM AUTHOR]

This paper considers the problem of finding suitable sites for wind farms in a region of Catalonia (Spain). The evaluation criteria are structured into a hierarchy that identifies several intermediate sub-goals dealing with different points of view. Therefore, the recent ELECTRE-III-H hierarchical multi-criteria analysis method is proposed as a good solution to help decision-makers. This method establishes an order among the set of possible sites for the wind farms for each sub-goal. ELECTRE-III-H aggregates these orders into an overall order using different parameters. The procedure is based on the construction and exploitation of a pairwise outranking relation, following the principles of concordance (i.e. majority rule) and discordance (i.e. respect for the minority opinions). This paper makes two main contributions. First, it contributes to the ELECTRE-III-H method by studying its mathematical properties for the construction of outranking relations. Second, the case study is solved and its results show that we can effectively represent and manage the overall influence of the various criteria on the global result at different levels of the hierarchy. The paper compares different scenarios with strict, normal, and optimistic preference, indifference and veto thresholds. Results show that the best site differs for technical, economic, environmental, and social intermediate criteria. Therefore, the best overall solution changes depending on the preference and veto thresholds fixed at the intermediate level of the hierarchy. [ABSTRACT FROM AUTHOR]

Understanding customers' decision and behavior is the crux of marketing. Despite the broad applications of weighted sum approaches, like conjoint analysis, sophisticated methodological approaches are under-researched in this field. Conversely, multi-criteria decision making's (MCDM) objective is to focus on and forecast these decisions. Based on the Choquet integral, this paper presents an effective and precise calculation method to understand real customers' decision making and to overcome the weighted sum method's limitations. We compare the weighted sum approach with stable and instable Choquet integral methods in three experimental studies. Our results indicate that the weighted sum approach is valuable in pure order-related applications. In quantitative comparisons, both the stable and instable Choquet integral approaches match the decision makers' preferences more closely than the weighted sum approach. The paper demonstrates that well-developed traditional approaches have their merits and can still be applied in the right context. [ABSTRACT FROM AUTHOR]

In recent years, decision makers, policy analysts, and other actors, have become increasingly aware of sustainability, and begun to combine economic, social and environmental criteria in their efforts to maintain competitiveness, long-term growth and development. In multiple stakeholder settings, the presence of diverse objectives and conflicting criteria often leads to a complex multi-criteria decision problem. The multi-criteria decision analysis (MCDA) offers an integrated framework to model and study sustainability criteria and related inter-criteria relationships. In this paper, we review some of the most significant literature on environmental sustainability, and categorise it to show how and why MCDA models are widely used and becoming increasingly popular. Our systematic analysis suggests that, there has been significant growth in environmental applications of MCDA in diverse areas, ranging from energy management and policy to land use, recycling management and sustainable tourism. Among the various MCDA methods and techniques, analytical hierarchy process, TOPSIS, and goal programming are the most frequently used approaches. Many authors use a combination of different MCDA techniques to balance various factors important to achieve sustainability related goals. We expect sustainability related criteria to be an essential consideration in most future multi-criteria models. [ABSTRACT FROM AUTHOR]

A single-valued neutrosophic multi-set is characterized by a sequence of truth membership degrees, a sequence of indeterminacy membership degrees and a sequence of falsity membership degrees. Nature of a single-valued neutrosophic multi-set allows us to consider multiple information in the truth, indeterminacy and falsity memberships which is pretty useful in multi-criteria group decision making. In this paper, we consider sequences of intuitionistic fuzzy values instead of numbers to define the concept of intuitionistic fuzzy-valued neutrosophic multi-set. In this manner, such a set gives more powerful information. We also present some set theoretic operations and a partial order for intuitionistic fuzzy-valued neutrosophic sets and provide some algebraic operations between intuitionistic fuzzy-valued neutrosophic values. Then, we develop two types of weighted aggregation operators with the help of intuitionistic fuzzy t-norms and t-conorms. By considering some well-known additive generators of ordinary t-norms, we give the Algebraic weighted arithmetic and geometric aggregation operators and the Einstein weighted arithmetic and geometric aggregation operators that are the particular cases of the weighted aggregation operators defined via general t-norms and t-conorms. We also define a simplified neutrosophic valued similarity measure and we use a score function for simplified neutrosophic values to rank similarities of intuitionistic fuzzy-valued neutrosophic multi-values. Finally, we give an algorithm to solve classification problems using intuitionistic fuzzy-valued neutrosophic multi-values and proposed aggregation operators and we apply the theoretical part of the paper to a real classification problem. [ABSTRACT FROM AUTHOR]

Life cycle sustainability assessment (LCSA) is an assessment method capable of supporting decision makers toward a more sustainable system. In this paper, a systematic literature review regarding LCSA application in the energy field was performed. The main challenges, methodological approaches, and sustainability indicators used to perform LCSA studies in this sector were highlighted. Peer-reviewed articles published until December 2020 were considered. The research portfolio consisted of 34 publications. According to the results, the energy sector functions as a platform for LCSA application and methodological development, as the number of studies applying this methodology in energy-related systems grew exponentially over the years. The review suggests that the choice of the life cycle concepts (system boundary, impact categories, etc.) is a critical point, as basically, every study presented different characteristics of life cycle studies. An even bigger diversity regarding sustainability indicators was found, especially regarding the social and economic pillars. A trend in the application of multi-criteria decision analysis (MCDA) to integrate results and facilitate decision- and policy-making processes was identified. Future studies could focus on the integration between LCSA other methods, identify solutions for the system boundaries interaction across sustainability dimensions, and develop further case studies, specially by combining LCSA and MCDA. [ABSTRACT FROM AUTHOR]

Pairwise comparisons have been a long-standing technique for comparing alternatives/criteria and their role has been pivotal in the development of modern decision-making methods such as the Analytic Hierarchy/Network Process (AHP/ANP), the Best-Worst method (BWM), PROMETHEE and many others. Pairwise comparisons can be performed within several frameworks such as multiplicative, additive and fuzzy representations of preferences, which are particular instances of a more general framework based on Abelian linearly ordered groups. Though multiplicative, additive and fuzzy representations of preferences are widely used in practice, it is unknown whether decision makers are equally precise in the three aforementioned representations when they measure objective data. Therefore, the aim of this paper is to design, carry out and analyse an experiment with over 200 respondents (undergraduate university students) from two countries, Czechia and Italy, to compare precision of the respondents in all three representations. In the experiment, respondents pairwise compared (by approximation) the areas of four geometric figures and then, the imprecision of their assessments was measured by computing the distance with the exact pairwise comparisons. We grouped the respondents in such a way that each participant was allowed to deal with a unique type of representation. The outcomes of the experiment indicate that the multiplicative approach is the most precise. [ABSTRACT FROM AUTHOR]

Natural disasters such as earthquakes endanger human lives and infrastructure, particularly in urban areas. With the advancements in science and technology in understanding natural hazards, recent studies have attempted to mitigate them by mapping the risks using geospatial technology. In this paper, we attempt to integrate the multi-criteria decision-making (MCDM) models, namely the Analytical Hierarchy Process (AHP) and the Criteria Importance Through Inter-criteria Correlation (CRITIC), besides using the artificial neural network (ANN) to assess the seismic risk in the eastern coast of India. The AHP-CRITIC technique is used to evaluate the earthquake coping capacity and vulnerability and has been further used to generate a training base for earthquake probability mapping by ANN. The earthquake probability and spatial intensity information are used to develop the hazard map. Following that, integrating vulnerability, hazard and coping capacity spatial information assessed earthquake risk. Our results indicate that approximately 5% of the study area is at high risk, whilst more than 11% of the population is at high risk due to seismic induced hazards. The area under the curve of the receiver operating characteristic curve is 0.85, which indicates reliable results. The results of this study may help various agencies involved in planning, development and disaster mitigation to develop seismic hazard mitigation methods by better understanding their impacts on the eastern coastal region of India. [ABSTRACT FROM AUTHOR]

Global warming, climate change, and social problems are the worst human-induced sustainability issues that economies across the globe have witnessed. Water pollution, greenhouse effect, poor working conditions, child labour and lack of coordination among channel partners have caused the considerable interruptions in the supply chain network. The purpose of the paper is to identify critical factors affecting behavioural and sustainable supply chain coordination and evaluate strategies for risk reduction in the supply chain coordination in the context of digitization. This study purposes a novel supply chain coordination framework which consists of four themes such as system, actor, objective and action on which the success or the failure of supply chain can be contingent. Our study integrates multi-criteria decision approach using Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) to investigate factors that affected the behavioural and sustainable supply chain coordination in the context of digitization. The Fuzzy-AHP method qualified to hierarchically rank the factors based on the relative fuzzy weightage while Fuzzy-DEMATEL established the inter-relationships among the factors and classified them into cause and effect groups. The findings of our study identified the Environmental performance and decarbonization as the most significant factor and the speed to market as the least important factor in developing behavioural and sustainable supply chain coordination in the context of digitization. Our analysis from Fuzzy AHP-DEMATEL approach reveal that the social preferences (power balance, reciprocity, fairness) is a significant causal factor which can effectively abolish the issues plaguing behavioural and sustainable supply chain coordination in the context of digitization. The results from our study aim to facilitate decision makers in cultivating a sustainable supply chain framework that can boost trust among the channel partners environmental performance, social performance and channel efficiency of the supply chain, thereby ensuring sustainability and socio welfare of all the supply chain. [ABSTRACT FROM AUTHOR]

The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW) are among the most employed approaches for aggregating performances in Multi-Criteria Decision-Making (MCDM). TOPSIS and SAW are two MCDM methods based on the value function approach and are often used in combination with other MCDM methods in order to produce rankings of alternatives. In this paper, first, we analyse some common features of these two MCDM methods with a specific reference to the additive properties of the value function and to the sensitivity of the value function to trade-off weights. Based on such methodological insights, an experimental comparison of the results provided by these two aggregation methods across a computational test is performed. Specifically, similarities in rankings of alternatives produced by TOPSIS and SAW are evaluated under three different Minkowski distances (namely, the Euclidean, Manhattan and Tchebichev ones). Similarities are measured trough a set of statistical indices. Results show that TOPSIS, when used in combination with a Manhattan distance, produces rankings which are extremely similar to the ones resulting from SAW. Similarities are also Experimental results confirm that rankings produced by TOPSIS methods are closer to SAW ones when similar formal properties are satisfied. [ABSTRACT FROM AUTHOR]

This paper aims to offer a group decision making (GDM) method based on intuitionistic triangular fuzzy information. Toward this end, a new ranking method for intuitionistic triangular fuzzy numbers (ITFNs) is firstly introduced based on the credibility measure theory, which can provide a total order on ITFNs. In view of the condition that interactions exist among the decision makers (DMs) or the criteria, the 2-additive Shapley intuitionistic triangular fuzzy aggregation (2ASITFA) operator is further proposed. According to the Wasserstein distance, a new distance measure of intuitionistic triangular fuzzy sets (ITFSs) is defined. Moreover, under the partial weak order information on the importance and interaction among the DMs and the criteria, the programming models are constructed to obtain the optimal 2-additive measure of the DMs and criteria respectively. Then, an intuitionistic triangular fuzzy multi-criteria GDM (ITFMCGDM) method is developed. At length, a practical example for evaluating the service quality of medical and nursing institutions (MNIs) is offered to illustrate the application of the proposed method. [ABSTRACT FROM AUTHOR]

The paper aims at developing a framework for decision-support to select a sustainable landfill site in Bardaskan City (Iran) by combining life cycle sustainability assessment (LCSA) concepts and geographic information system (GIS)-based multi-criteria decision-making (MCDM). Overall, 13 criteria were chosen (three constraints and 10 factors) and classified into three main aspects of sustainability (i.e., environmental, social, and economic) to achieve the research goals. Boolean and fuzzy logic were employed to standardize the classified constraints and factors, respectively. Analytic hierarchy process (AHP) was used to calculate the factors' weights and then suitability maps were produced using the GIS analysis. The layers were combined using simple additive weighting (SAW). Next, the most sustainable sites were obtained. The results indicated that distance from city backline, groundwater depth, and distance from rural areas were the most significant factors with the weight of 0.338, 0.141, and 0.129, respectively. The final map of suitable sites was created by classifying the SAW layer according to 75, 80, and 85% of suitability to show the high, medium, and low priority areas for landfill site selection, respectively. Therefore, integration of LCSA and GIS-based MCDM to select the sustainable landfill site for municipal solid waste (MSW) is highly important, which can be effectively employed in regional and urban planning to select the location of appropriate and sustainable landfills. [ABSTRACT FROM AUTHOR]

Rail transportation planning is a continuous, multi-phase, functioning scale that is based on reconstructing the spatial system, thus contributing to build a more quality-focused, long-term-oriented and balanced approach. This paper presents cartographic modelling and multi-criteria analysis (CMCA) for the optimum route/station location in accordance with selected criteria and constraints for rail transit system planning. The methodology is based on overlay analysis (cartographic modelling) to combine diverse criteria maps and the analytic hierarchy process (AHP) method for criteria weighting. The purpose of the study is to examine a GIS multiple-criteria decision-making (MCDM) framework by considering Stream, Geology, Slope, Land use and Population decision criteria. The decision modelling framework conceives an additional prominent approach by co-producing with the public, especially for underserved areas of low socio-economic status and public user expectations in the railway transport planning process. This model applied to a candidate metro line referred to as M 18 (Başakşehir-Esenyurt-Beylikdüzü) with eight railway stations for the preliminary stage evaluation. The outcomes of this research will close the gap by establishing a novel suitability framework which can be used as a preliminary analysis for transforming and developing urban rail transit networks. [ABSTRACT FROM AUTHOR]

Express packaging recycling (EPC) can migrate the pressures of environmental pollution and resource shortages, which can support the sustainable development of the online retail and express delivery industry. In this view, this paper introduces a hybrid MCDM (multi-criteria decision-making) framework combining fuzzy group FUCOM (fuzzy full consistency method), fuzzy GRC-DANP (grey relational coefficient-DEMATEL-ANP), and fuzzy EDAS (evaluation based on distance from average solution) techniques to prioritize the EPC patterns. Comparing with the related studies, this framework considers multiple criteria from different concerns for offering a comprehensive assessment. The three modified fuzzy MCDM methods use the triangular fuzzy number to address the uncertain decision-making environment; more importantly, they may make the following contributions to the complex decision-making concerning the EPC: (1). Fuzzy group FUCOM allows multiple decision-makers to take part in the evaluation of alternatives' performances; meanwhile, it can easily yet rationally quantify the qualitative evaluations into quantitative performances. (2). Fuzzy GRC-DANP provides an objective and reliable process to assign the weights to the interrelated criteria, by clarifying the interrelationships among the multi-criteria according to the datasets of the alternatives' performances. (3). Fuzzy EDAS offers a rational ranking result by resorting to a simplified compromise ranking logic while considering the uncertainty in the prioritization. To test the feasibility of the framework, three typical EPC patterns, i.e., the door-to-door pattern, recycling bins pattern, and recycling location pattern, were investigated by using a ten-criterion assessment system that embraces the concerns from the customers, costs, technical, and environmental aspects. The results signify the recycling bins pattern acts better than the others. Besides, the effectiveness of the framework was confirmed by running the sensitivity analysis and result comparison. [ABSTRACT FROM AUTHOR]

There are many influencing factors and characterization indicators of the laser shock processing (LSP) quality make it difficult to evaluate the processing quality comprehensively and economically. Furthermore, there is no systematic and comprehensive evaluation system for the LSP quality. Therefore, this article combines the coefficient of variation (CV) and Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods to establish an evaluation model. The model was used to evaluate the strengthening quality of the FGH95 superalloy to manufacture helicopter turbine disks after the LSP orthogonal test. The results show that when the laser energy is 8 J, the beam diameter is 5 mm and the number of impacts is 2, the compromise decision indicator value is 0.1806, with the relatively best strengthening effect for the FGH95 superalloy. Under the index weight set in this paper, the comprehensive material properties of the FGH95 superalloy is improved by 3.25 times compared with the unimpacted sample. The CV-VIKOR method has good stability and reliability, enabling efficient, comprehensive, and scientific evaluation and comparison of enhanced quality of different processed samples. This method has an essential reference and guiding significance for reducing the experimental workload, saving experimental costs, and promoting and applying the LSP technology. [ABSTRACT FROM AUTHOR]

The world is currently confronting one of its biggest environmental challenges: combating climate change. Coastal zones are one of the areas thought to be most sensitive to current and future climate change threats. The paper integrates Remote Sensing (RS), Geographic Information System (GIS) techniques, and Multi-Criteria Decision Analysis (MCDA) to detect vulnerable areas from climate change impacts in coastal zones in order to recommend adaptation systems in new coastal zones that can withstand various climatic changes. The proposed decision-making framework was developed in three phases: 1) climate data collection and processing; 2) Coastal Climate Impact Assessment (CCIA) model development; and 3) implementation and adaptation system selection. The climate data collection and processing phase involves determining the most significant climate change parameters and their indicators that affect coastal zone stability, extracting climatic data indicators from different climate database sources, and prioritizing the selected indicators. The indicators' weights were estimated using the Analytical Hierarchy Process (AHP) through a questionnaire survey shared with experts in climate change impacts. A CCIA model development phase involves the formulation of the proposed model using GIS technique to discover the vulnerable areas according to the most dominant impact. The implementation and adaptation system selection phase involves the application of the framework to Al-Alamein New City in Egypt. A sensitivity analysis was conducted to measure the behavior of several climate change parameters to identify the most critical parameter for climate change in Al-Alamein New City. The results showed that the geology of the region is the most crucial component influenced by climate change. It is capable of producing a very sensitive area in the coastal zone while also taking other factors into account. When creating new urban neighborhoods, the erosion of the shoreline is the least important factor to consider. This is because coastal deterioration is caused by both the influence of metrological data on the region and the impact of human activity. Shoreline deterioration will be reduced if climate conditions are maintained while limiting the impact of human activities. To adapt to the long-term effects of climate change on coastal zones, a combination of soft and hard protection systems should be considered. [ABSTRACT FROM AUTHOR]

Highlights from the article: Multiple attribute decision making (MADM), as one of the most important parts of modern decision-making science, has been widely studied and successfully applied to many fields. Because of the need for better and detailed membership functions, ordinary fuzzy sets have been extended to intuitionistic fuzzy sets, interval-valued Intuitionistic fuzzy sets, hesitant fuzzy sets, linguistic interval-valued Intuitionistic fuzzy sets, Pythagorean fuzzy sets. After its appearance, several extensions such as interval-valued Pythagorean fuzzy sets, hesitant Pythagorean fuzzy sets, Linguistic Pythagorean fuzzy sets come into the play to solve the decision-making problems.

Modern manufacturing's objective is to guarantee quality while lowering production costs and increasing productivity. In this context, the selection of cutting materials is important in increasing productivity due to their wide range of applications. In this paper, when machining AISI 4140 alloy steel, an experimental study is presented to find the cutting conditions that result in minimum Ra, Vb, and maximum MRR values. Different optimization methods are used, namely, Taguchi, grey relational analysis (GRA), technique by order of preference by similarity to ideal solution (TOPSIS), and multi-objective optimization ratio analysis (MOORA). Taguchi's L16 design was used to arrange 16 experiments. Cutting speed (Vc), feed rate (f), and depth of cut (ap) were the input parameters, with four levels for each cutting parameter. The feed rate and cutting speed had the greatest effect on Ra and Vb, according to an ANOVA analysis of the experimental results. MRR was significantly affected by the depth of cut and feed rate. To achieve the minimum surface roughness, flank wear, and maximum material removal rate, the cutting speed, feed rate, and depth of cut were required to be 250 m/min, 0.11 mm/rev, and 1.4 mm, respectively, according to the optimization results. [ABSTRACT FROM AUTHOR]

Based on the encouragement and increasingly recycling demands of the Chinese governments, online recycling platforms based on B2C, such as loving recycling app, waste recycling alliance app, have emerged as the times require. As an indispensable part of online recycling, recycling app evaluation plays a vital role in user acceptance of the innovative recycling way. As we all know, app evaluation is a typical multiple criteria decision making (MCDM) problem involving many complicated criteria. This paper aims to propose an integrated MCDM method to solve this issue under a probabilistic linguistic context. Firstly, a special evaluation criteria system is constructed for measuring apps' performance, which includes five main criteria namely technical feature, safety, interface design, basic requirement, service quality, as well as 12 sub-criteria. Then, we integrated the best-worst method (BWM) and entropy method with the probabilistic linguistic term to determine the subjective and objective weights. And then the comprehensive weights are calculated by multiplicative integration method. Afterwards, the MULTIMOORA method with the Borda rule, is used to rank alternatives and identify the optimal recycling app. Finally, the assessment of the four recycling apps' performance in Beijing is presented to illustrate the validity and rationality of the proposed approach in practical applications. [ABSTRACT FROM AUTHOR]

The International Civil Aviation Organization has recently established new standards for the aeronautical telecommunication network using Internet protocol suite (ATN/IPS). As ATN services may operate on shared data communication links, optimizing the use of the shared resources has become fundamental to ensure that applications operate adequately. In this context, load balancing for ATN/IPS can be considered in an attempt to optimize the use of links based on their capacities. The literature is scarce of network management studies in which load balancing is taken into account. In this paper, we propose an integrated model for managing ATN/IPS links. In addition to objective parameters, we define subjective parameters of the model through the voluntary participation of air traffic controllers. The well-known multi-criteria decision making method Analytic Hierarchy Process was employed to define the subjective parameters of the integrated model, which met the requirements of communication services and applications of the aeronautical network. The network selection problem was then modeled in a multi-objective optimization problem after combining the criteria by using Simple Additive Weighting method. Computational experiments with real data from Brazilian ATN (ATN-Br) were performed. The ε -constraint method was applied to solve the multi-objective problem by varying the balance levels of the network. The results of the experiments show that the proposed integrated model maintains links with a usage rate closer to the trade-off point. In addition, the use of objective and subjective criteria allows the model to effectively prioritize critical communications in link degraded scenarios, which does not happen in the baseline model, in which priorities are pre-defined. [ABSTRACT FROM AUTHOR]

The aim of this paper is to develop useful likelihood-based assignment methods for addressing multiple criteria decision-making problems within the environment of interval-valued intuitionistic fuzzy sets. Based on the likelihoods of interval-valued intuitionistic fuzzy preference relations, this paper determines the mean likelihoods of outranking relations and presents a mean likelihood determination method for generating a set of criterion-wise rankings of alternatives. By employing the concepts of rank frequency matrices and (ordinary) rank contribution matrices, this paper establishes a likelihood-based linear assignment model for multiple criteria decision analysis in the interval-valued intuitionistic fuzzy context. Additionally, this paper propounds two likelihood-based assignment models for handling incomplete and conflicting certain information of importance weights. These models can transform the criterion-wise ranks into the overall ranks for determining the optimal priority ranking of the alternatives. The feasibility and applicability of the proposed methods are illustrated with a practical problem of selecting a bridge construction method which involves various preference types. Finally, this paper conducts a comparative analysis with previous assignment-based methods in an interval-valued intuitionistic fuzzy setting to validate the effectiveness and advantages of the proposed methods. [ABSTRACT FROM AUTHOR]