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Optimization is a process of minimizing or maximizing a given objective function under specified constraints. In multi-objective optimization (MOO), multiple conflicting functions are optimized within defined criteria. Numerous MOO techniques have been developed utilizing various meta-heuristic methods such as Evolutionary Algorithms (EAs), Genetic Algorithms (GAs), and other biologically inspired processes. In a cooperative environment, a Pareto front is generated, and an MOO technique is applied to solve for the solution set. On other hand, Multi-Criteria Decision Making (MCDM) is often used to select a single best solution from a set of provided solution candidates. The Multi-Criteria Decision Making–Pareto Front (M-PF) optimizer combines both of these techniques to find a quality set of heuristic solutions. This paper provides an improved version of the M-PF optimizer, which is called the elite Multi-Criteria Decision Making–Pareto Front (eMPF) optimizer. The eMPF method uses an evolutionary algorithm for the meta-heuristic process and then generates a Pareto front and applies MCDM to the Pareto front to rank the solutions in the set. The main objective of the new optimizer is to exploit the Pareto front while also exploring the solution area. The performance of the developed method is tested against M-PF, Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), and Non-Dominated Sorting Genetic Algorithm-III (NSGA-III). The test results demonstrate the performance of the new eMPF optimizer over M-PF, NSGA-II, and NSGA-III. eMPF was not only able to exploit the search domain but also was able to find better heuristic solutions for most of the test functions used. [ABSTRACT FROM AUTHOR]

One of the crucial steps in the multi-criteria decision analysis involves establishing the importance of criteria and determining the relationship between them. This paper proposes an extended Hellwig's method (H_EM) that utilizes entropy-based weights and Mahalanobis distance to address this issue. By incorporating the concept of entropy, weights are determined based on their information content represented by the matrix data. The Mahalanobis distance is employed to address interdependencies among criteria, contributing to the improved performance of the proposed framework. To illustrate the relevance and effectiveness of the extended H_EM method, this study utilizes it to assess the progress toward achieving Sustainable Development Goal 4 of the 2030 Agenda within the European Union countries for education in the year 2021. Performance comparison is conducted between results obtained by the extended Hellwig's method and its other variants. The results reveal a significant impact on the ranking of the EU countries in the education area, depending on the choice of distance measure (Euclidean or Mahalanobis) and the system of weights (equal or entropy-based). Overall, this study highlights the potential of the proposed method in addressing complex decision-making scenarios with interdependent criteria. [ABSTRACT FROM AUTHOR]

This paper introduces a pioneering model that merges coupled Markov chains (CMC) with the fuzzy analytic hierarchy process (FAHP) to enhance multi-criteria decision making (MCDM) amidst the dynamic interplay of criteria. Traditional MCDM frameworks often lack the granularity to manage the intricate and changing relationships among criteria. Our model addresses this gap by integrating fuzzy numbers into AHP, providing a nuanced means to handle the inherent uncertainty of decision criteria. The application of the Kronecker product in CMC enriches our approach, offering a data-driven analysis while mitigating excessive dependence on subjective expert opinion. A comprehensive numerical example underlines the model's improved decision-making accuracy and efficiency, marking a substantial advancement in MCDM methodologies. This research contributes to the field by presenting a sophisticated yet practical framework for dynamic decision analysis in complex uncertain environments. [ABSTRACT FROM AUTHOR]

This paper proposes the method pELECTRE Tri, a novel probabilistic Multi-Criteria Decision Making (MCDM) method using the traditional ELECTRE Tri, probability distribution, and Monte Carlo simulation to support informed decision-making in complex and uncertain decision environments. The proposed method is illustrated through a case study involving the renovation of three social housing buildings. The paper provides new insights into the application of probabilistic sorting MCDM in the context of energy efficiency in buildings and highlights the benefits of using probabilities rather than crisp values to categorize alternatives enabling stakeholders to make better use of available resources, especially when dealing with a large dataset of energy measures with different features. The methodology implemented in Python (DOI: 10.5281/zenodo.7967655) is available as an open source. [ABSTRACT FROM AUTHOR]

Machine learning algorithms are valuable tools for solving a wide variety of complex engineering problems. Usually, those problems have multiple criteria to fulfill, but such machine learning-based solutions are usually optimized using a single criterion. In such instances, a multi-objective optimization-based approach could bring interesting solutions by determining a set of Pareto-optimal solutions with different trade-off. Therefore, a multi-criteria decision-making process must be carried out. To the authors' present knowledge, multi-criteria decision-making is yet to be fully explored for selecting preferable Pareto-optimal machine learning models after the training step. Therefore, this paper proposes applying and comparing five different multi-criteria decision-making techniques for selecting a preferred machine learning model. Additionally, an ensemble-based framework is proposed to cope with the difficulty of selecting parameters for such techniques. Those tools are tested on a complex real-world drinking-water quality monitoring problem. Results based on the F 1 score indicate that via a multi-criteria decision-making process (F 1 = 0. 5 6), it is possible to select better solutions than single-criterion approaches (F 1 = 0. 5 5). Moreover, the proposed ensemble framework is able to mitigate the difficulty in defining preferences and regions of interest, achieving competitive solutions. [ABSTRACT FROM AUTHOR]

Hellwig's method is a multi-criteria decision-making technique designed to facilitate the ranking of alternatives based on their proximity to the ideal solution. Typically, this approach calculates distances using the Euclidean norm, assuming implicitly that the considered criteria are independent. However, in real-world situations, the assumption of criteria independence is rarely met. The paper aims to propose an extension of Hellwig's method by incorporating the Mahalanobis distance. Substituting the Euclidean distance with the Mahalanobis distance has proven to be effective in handling correlations among criteria, especially in the context of asymmetrical relationships between criteria. Subsequently, we investigate the impact of the Euclidean and Mahalanobis distance measures on the several variants of Hellwig procedures, analyzing examples based on various illustrative data with 10 alternatives and 4 criteria. Additionally, we examine the influence of three normalization formulas in Hellwig's aggregation procedures. The investigation results indicate that both the distance measure and normalization formulas have some impact on the final rankings. The evaluation and ranking of alternatives using the Euclidean distance measure are influenced by the normalization formula, albeit to a limited extent. In contrast, the Mahalanobis distance-based Hellwig's method remains unaffected by the choice of normalization formulas. The study concludes that the ranking of alternatives is strongly dependent on the distance measure employed, whether it is Euclidean or Mahalanobis. The Mahalanobis distance-based Hellwig method is deemed a valuable tool for decision-makers in real-life situations. It enables the evaluation of alternatives by considering interactions between criteria, providing a more comprehensive perspective for decision-making. [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]

Some decision‐making problems are required to be analysed using insufficient and vague information under an extended space of fuzziness, considering flexibility in the decision‐making process and the interdependency and interaction between the criteria. To tackle these challenges, a spherical fuzzy set (SFS), which is an extension of the ordinary picture fuzzy set (PFS), can be used to fulfil the requirement of an extended space of fuzziness by quantifying uncertainty. Similarly, the Frank operations can provide flexibility to the decision‐making process due to the involvement of a parameter, whereas the Choquet integral considers all possible interactive characteristics between different criteria. Therefore, this paper integrates these three important concepts to make more sound and realistic decisions by extending the existing arithmetic operation for spherical fuzzy numbers (SFNs) using Frank t‐norm and t‐conorm. In addition, the paper introduces some novel Choquet‐Frank aggregation operators, such as spherical fuzzy Choquet‐Frank averaging (SFCFA) and spherical fuzzy Choquet‐Frank geometric (SFCFG). To demonstrate the effectiveness of the proposed operators, a multi‐criteria decision making (MCDM) problem related to the selection of an enterprise resource planning (ERP) system is analysed for the available five options χ1,χ2,χ3,χ4, and χ5. Sensitivity analysis is performed to investigate the impact of taking variation in parameter values (θ) on aggregated values. Results confirmed that the best alternatives for SFCFA and SFCFG operators are χ3 and χ5, respectively, while χ2 is the worst alternative for both these operators. To show the effectiveness of the proposed operators, a comparative analysis has been performed to compare the results obtained from other existing aggregation operators. Results concluded that the findings resemble most of the existing operators which confirms the feasibility of the proposed operators. [ABSTRACT FROM AUTHOR]

Inventory management presents numerous challenges for many supply chains as they are becoming more complex and composed of multiple stages. Using appropriate multi-echelon inventory management policies allows supply chains to deliver the required level of responsiveness efficiently by optimizing inventory levels across the entire network and improving customer service levels. This paper provides a Multi-Criteria Decision Making (MCDM) approach for the multi-echelon inventory system selection problem. The scope of this paper is limited to the case of Distribution systems. The suggested approach identifies for a given supply chain configuration, a set of selection criteria related to supply chain costs and overall responsiveness. These criteria are used to compare and choose the best alternative from different multiechelon distribution inventory system configurations by using a suitable MCDM method. Eight different multi-echelon distribution inventory system alternatives are generated. Each one is a combination of three main inventory policies: (i) replenishment policies, (ii) ordering policies, and (iii) safety stock allocation policies. The suggested approach is illustrated in the case of the pharmaceuticals products supply chain in the public sector in Morocco. Depending on the decision problem nature and other criteria, the AHP method proved to be the suitable MCDM method for selecting the best multi-echelon inventory system for the Moroccan pharmaceutical products supply chain. The analysis indicates that assigning inventory to the most downstream facilities close to patients and adopting an installation stock ordering policy implemented by a decentralized decision system is the best option for the supply chain considered in the case study. [ABSTRACT FROM AUTHOR]

Software testing plays a significant role in various software development phases. There are so many software testing techniques available. Selecting the most suitable software testing technique based on multiple factors is challenging for software practitioners. This paper proposes an MCDM-based hybrid approach for selecting the most appropriate software testing technique among various available software testing techniques, considering multiple factors such as cost, schedule, resources, etc. Because of the involvement of multiple factors, the problem of selecting the most appropriate software testing technique can be modeled as an MCDM problem. This study proposes a hybrid approach by integrating two MCDM methods BWM (Best-Worst Method) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), for evaluating various software testing techniques considering multiple factors altogether. For the applicability of the proposed approach, an experimental study was conducted using seven software testing techniques and six evaluation criteria. Results show the proposed approach can be used as an efficient tool for selecting the most suitable software testing technique among various available testing techniques in the presence of multiple factors. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the concept of circular Pythagorean fuzzy set (value) (C-PFS(V)) as a new generalization of both circular intuitionistic fuzzy sets (C-IFSs) proposed by Atannassov and Pythagorean fuzzy sets (PFSs) proposed by Yager. A circular Pythagorean fuzzy set is represented by a circle that represents the membership degree and the non-membership degree and whose centre consists of non-negative real numbers μ and ν with the condition μ 2 + ν 2 ⩽ 1. A C-PFS models the fuzziness of the uncertain information more properly thanks to its structure that allows modelling the information with points of a circle of a certain centre and a radius. Therefore, a C-PFS lets decision makers to evaluate objects in a larger and more flexible region and thus more sensitive decisions can be made. After defining the concept of C-PFS we define some fundamental set operations between C-PFSs and propose some algebraic operations between C-PFVs via general triangular norms and triangular conorms. By utilizing these algebraic operations, we introduce some weighted aggregation operators to transform input values represented by C-PFVs to a single output value. Then to determine the degree of similarity between C-PFVs we define a cosine similarity measure based on radius. Furthermore, we develop a method to transform a collection of Pythagorean fuzzy values to a C-PFS. Finally, a method is given to solve multi-criteria decision making problems in circular Pythagorean fuzzy environment and the proposed method is practiced to a problem about selecting the best photovoltaic cell from the literature. We also study the comparison analysis and time complexity of the proposed method. [ABSTRACT FROM AUTHOR]

Public–private partnership (PPP) infrastructure projects have attracted attention over the past few years. In this regard, the selection of private partners is an integral decision to ensure its success. The selection process needs to identify, scrutinize, and pre-qualify potential private partners that sustain the greatest potential in delivering the designated public–private partnership projects. To this end, this research paper proposes an integrated multi-criteria decision-making (MCDM) model for the purpose of selection of the best private partners in PPP projects. The developed model (HYBD_MCDM) is conceptualized based on two tiers of multi-criteria decision making. In the first tier, the fuzzy analytical network process (FANP) is exploited to scrutinize the relative importance of the priorities of the selection criteria of private partners. In this respect, the PPP selection criteria are categorized as safety, environmental, technical, financial, political policy, and managerial. In the second tier, a set of seven multi-criteria decision-making (MCDM) algorithms is leveraged to determine the best private partners to deliver PPP projects. These algorithms comprise the combined compromise solution (CoCoSo), simple weighted sum product (WISP), measurement alternatives and ranking according to compromise solution (MARCOS), combinative distance-based assessment (CODAS), weighted aggregate sum product assessment (WASPAS), technique for order of preference by similarity to ideal solution (TOPSIS), and FANP. Thereafter, the Copeland algorithm is deployed to amalgamate the obtained rankings from the seven MCDM algorithms. Four real-world case studies are analyzed to test the implementation and applicability of the developed integrated model. The results indicate that varying levels of importance were exhibited among the managerial, political, and safety and environmental criteria based on the nature of the infrastructure projects. Additionally, the financial and technical criteria were appended as the most important criteria across the different infrastructure projects. It can be argued that the developed model can guide executives of governments to appraise their partner's ability to achieve their strategic objectives. It also sheds light on prospective private partners' strengths, weaknesses, and capacities in an attempt to neutralize threats and exploit opportunities offered by today's construction business market. [ABSTRACT FROM AUTHOR]

Engineering and technological breakthroughs in sustainability play a crucial role in reducing carbon emissions. An important aspect of this is the active participation of enterprises in addressing carbon reduction as a systemic approach. In response to government incentives in the People's Republic of China, Chinese enterprises have developed carbon reduction systems to align their organizational goals with national long-term plans. This paper evaluates the carbon reduction schemes employed by six companies as a multi-criteria decision-making (MCDM) problem. To this end, we propose a new hybrid MCDM method called the grey-MEREC-MAIRCA method. This method combines the recently developed method based on the removal effects of criteria (MEREC) for weighting and multi-attribute ideal-real comparative analysis (MAIRCA) based on the grey system theory. The proposed hybrid method provides the additional benefit of accounting for uncertainty in decision making. Notable findings of this research, based on the decision-maker scores, are that the control of direct carbon emissions and energy-saving efficiency are top priorities. In contrast, committing to corporate social responsibility through carbon public welfare and information disclosure are considered lesser priorities. Furthermore, the ranking results obtained using this method are compared with those from the classical weighted sum model and the technique for order preference by similarity to ideal solution (TOPSIS), confirming the selection of the best company. Despite the limitation of the proposed method and the additional steps needed in the evaluation, it opens up opportunities for future research to develop simpler MCDM methods under uncertainty. [ABSTRACT FROM AUTHOR]

The scientific selection of a third-party reverse logistics service provider (3PRLP) is helpful for enterprises to obtain the expected ecological and economic benefits. Different enterprises have different requirements for 3PRLP selection and, thus, should adopt personalized and simplified evaluation criteria. However, there is a lack of research on criteria screening. Therefore, this paper proposes a criteria screening method based on a rough set for the first time. The 3PRLP selection is a multi-criteria decision making (MCDM) problem in essence, and different criteria can be expressed in different forms. The existing research mostly uses one method for 3PRLP selection, lacking the comprehensive application of various methods. In this paper, various criteria values are transformed into intuitionistic fuzzy numbers (IFNs) for the comparison and combination of various intuitionistic fuzzy MCDM methods. In terms of criteria weighting, a subjective weighting method based on an analytical network process (ANP) is proposed due to the possible correlation between the criteria at the same level. Meanwhile, an objective weighting method based on intuitionistic fuzzy entropy is proposed. The subjective and objective weights are integrated to form the more scientific combination weights. Combining the modeling principles of different intuitionistic fuzzy MCDM methods, the representative methods under each principle are chosen to build a combination evaluation idea that integrates multiple single evaluation models, and the specific evaluation steps are given, including the single evaluation, Kendall compatibility test, combination evaluation, and Spearman consistency test. An illustrative example of 3PRLP selection is provided to verify the feasibility of the methods of criteria screening and weighting and the combination evaluation idea. [ABSTRACT FROM AUTHOR]

Recently, the notion of a three-way fuzzy set is presented, inspired by the basic ideas of three-way decision and various generalized fuzzy sets, including lattice-valued fuzzy sets, partial fuzzy sets, intuitionistic fuzzy sets, etc. As the new theory of uncertainty, it has been used in attribute reduction and as a new control method for the water level. However, as an extension of a three-way decision, this new theory has not been used in multi-criteria decision making (MCDM for short). Based on the previous work, in this paper, we present rough set models based on three-way fuzzy sets, which extend the existing fuzzy rough set models in both complete and incomplete information systems. Furthermore, the new models are used to solve the issue of MCDM. Firstly, three-way fuzzy relation rough set and three-way fuzzy covering rough set models are presented for complete and incomplete information systems. Because almost all existing fuzzy rough set models are proposed under complete information, the new proposed models can be seen as a supplement to these existing models. Then, a relationship between the three-way fuzzy relation rough set and the three-way fuzzy covering rough set is presented. Finally, a novel method for the issue of MCDM is presented under the novel three-way fuzzy rough set models, which is used in paper defect diagnosis. [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]

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]

The evaluation of cultural websites is a complicated procedure that depends on several criteria. The main contribution of this paper is on showing how this process may be implemented. For this reason, different multi-criteria decision-making methods are combined and compared for processing the results of the evaluation. More specifically, the paper provides the criteria for evaluating a website of cultural heritage and presents the application of Analytical Hierarchy Process for estimating the weights of the criteria. Then, it compares two different multi-criteria decision-making models, fuzzy simple additive weighting and fuzzy weighted product model, for being combined with Analytical Hierarchy Process and processing the results of the evaluation. The evaluation involves 29 websites of the conservation labs of the international museums and useful conclusions are extracted about the application of all methods and the combination of Analytical Hierarchy Process with fuzzy simple additive weighting and fuzzy weighted product model. [ABSTRACT FROM AUTHOR]

Copyright of Military Technical Courier / Vojnotehnicki Glasnik is the property of Military Technical Courier / Vojnotehnicki Glasnik and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The ranking of intuitionistic fuzzy numbers is paramount in the decision making process in a fuzzy and uncertain environment. In this paper, a new ranking function is defined, which is based on Robust's ranking index of the membership function and the non-membership function of trapezoidal intuitionistic fuzzy numbers. The mentioned function also incorporates a parameter for the attitude of the decision factors. The given method is illustrated through several numerical examples and is studied in comparison to other already-existent methods. Starting from the new classification method, an algorithm for solving fuzzy multi-criteria decision-making (MCDM) problems is proposed. The application of said algorithm implies accepting the subjectivity of the deciding factors, and offers a clear perspective on the way in which the subjective attitude influences the decision-making process. Finally, a MCDM problem is solved to outline the advantages of the algorithm proposed in this paper. [ABSTRACT FROM AUTHOR]

Purpose: Single-valued neutrosophic sets (SVNSs) are efficient models to address the complexity issues potentially with three components, namely indeterminacy, truthness and falsity. Taking advantage of SVNSs, this paper introduces some new aggregation operators (AOs) for information fusion of single-valued neutrosophic numbers (SVNNs) to meet multi-criteria group decision-making (MCGDM) challenges. Design/methodology/approach: Einstein operators are well-known AOs for smooth approximation, and prioritized operators are suitable to take advantage of prioritized relationships among multiple criteria. Motivated by the features of these operators, new hybrid aggregation operators are proposed named as "single-valued neutrosophic Einstein prioritized weighted average (SVNEPWA) operator" and "single-valued neutrosophic Einstein prioritized weighted geometric (SVNEPWG) operators." These hybrid aggregation operators are more efficient and reliable for information aggregation. Findings: A robust approach for MCGDM problems is developed to take advantage of newly developed hybrid operators. The effectiveness of the proposed MCGDM method is demonstrated by numerical examples. Moreover, a comparative analysis and authenticity analysis of the suggested MCGDM approach with existing approaches are offered to examine the practicality, validity and superiority of the proposed operators. Originality/value: The study reveals that by choosing a suitable AO as per the choice of the expert, it will provide a wide range of compromise solutions for the decision-maker. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Natural Fibers is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Most of the practical applications that require optimization often involve multiple objectives. These objectives, when conflicting in nature, pose both optimization as well as decision-making challenges. An optimization procedure for such a multi-objective problem requires computing (computer-based search) and decision making to identify the most preferred solution. Researchers and practitioners working in various domains have integrated computing and decision-making tasks in several ways, giving rise to a variety of algorithms to handle multi-objective optimization problems. For instance, an a priori approach requires formulating (or eliciting) a decision maker's value function and then performing a one-shot optimization of the value function, whereas an a posteriori decision-making approach requires a large number of diverse Pareto-optimal solutions to be available before a final decision is made. Alternatively, an interactive approach involves interactions with the decision maker to guide the search towards better solutions (or the most preferred solution). In our tutorial and survey paper, we first review the fundamental concepts of multi-objective optimization. Second, we discuss the classic interactive approaches from the field of Multi-Criteria Decision Making (MCDM), followed by the underlying idea and methods in the field of Evolutionary Multi-Objective Optimization (EMO). Third, we consider several promising MCDM and EMO hybrid approaches that aim to capitalize on the strengths of the two domains. We conclude with discussions on important behavioral considerations related to the use of such approaches and future work. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Metodos Cuantitativos para la Economia y la Empresa is the property of Universidad Pablo de Olavide and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we apply a computational model for multicriteria decision making in traffic jam problems. First, we propose a system to determine the optimal shortcut road by reading the number of cars in each street using Radio Frequency Identification (RFID). Then, we have processed the data of traffic jam problems using Choquet integral with writing algorithm and computer program as a working procedure. [ABSTRACT FROM AUTHOR]

Properly assigning weights to decision makers in a group decision making environment is one of the essential processes of utmost importance as it can have a direct effect on the final outcome. This paper, basing on the entropy method, proposes a correct and efficient way to objectively assign weights to decision makers in a multi-criteria group decision making environment. Two approaches namely, constant and variable weighting, have been put forward whilst providing necessary proofs and numerical examples in order to show one of the existing ways in literature is erroneous as it is not resulting in weights that reflects entropy method’s basic intuition. [ABSTRACT FROM AUTHOR]

Population growth has become a serious problem in many countries, especially Egypt. Which leads to an increase in the population area and an increase in buildings, which then leads to several problems, including large energy consumption, increased pollution, traffic congest ion, and others. Therefore, many governments have resorted to using technology and applying it to build smart buildings to help save energy by using renewable energy to improve its impact on the environment, improve the quality of life of citizens, provide security and safety, and so on. The selection of smart buildings depends on many criteria. Since this problem is described as a multi-criteria decision-making (MCDM) problem, MCDM methods will be used in this paper. A hybrid method is presented to evaluate smart buildings. The first method, MEREC, was used to calculate the weights of criteria, and the VIKOR model was used for ranking alternatives. Then applying those weights to the CoCoSo, COPRAS, and TOPSIS methods for making comparisons using Spearman's correlation coefficients for ranking these four methods. All methods used are applied in the T2NN environment. [ABSTRACT FROM AUTHOR]

Due to the ever-increasing water scarcity problem across the globe, the treatment of wastewater is an important public health and socio-economic issue. Treating wastewater through proper technology is vital to protect the ecosystem from unsafe and contaminated matter available in wastewater. Identification of suitable wastewater treatment technologies is a complex Multi-Criteria Decision Making (MCDM) problem since it includes many conflicting assessment criteria. The objective of the paper is to construct an integrated model using the Analytical Hierarchy Process (AHP) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) for evaluating wastewater treatment technologies (WWTTs). AHP is applied to calculate criteria weights, and the VIKOR method is applied to prioritize and select the best WWTTs. The proposed model is applied to selecting the best WWTT among four alternatives and seven criteria. It is found that the proposed model yields better results when compared with other MCDM solutions. [ABSTRACT FROM AUTHOR]

Education is an essential component for nations preparing to take advantage of the opportunities and confront the challenges of the 21st century. Universities, colleges, and research centers must work effectively and efficiently to achieve maximum results. In order to provide a comparable and verifiable evaluation of such institutions' efforts, administrators need to adopt measurement tools such as those offered by multi-criteria decision-making (MCDM). The use of MCDM to solve complex real-world problems in the educational sector has dramatically increased in the past decade. This paper ranked the Engineering departments in a public university from 2019 to 2021 using combined MCDM methods between Analytical Hierarchy Analysis (AHP) and Ranking Alternatives by Perimeter Similarity (RAPS). The AHP technique assisted in the weighting for each evaluation criterion covered in this study. The RAPS technique assisted in ranking the Engineering departments using weights derived from the AHP technique. For the first time, the use of RAPS in the educational sector is presented in this paper. The findings revealed some of the departments under investigation's vulnerabilities, indicating that they require assistance from the institution's administration. Moreover, the results demonstrate that combining the AHP and RAPS techniques to evaluate and rank university departments is a successful method. [ABSTRACT FROM AUTHOR]

This paper proposes a new linguistic model called Linguistic q-Rung Orthopair fuzzy Z-number (LqROFZN), which combines the advantages of linguistic variables, Z-number and q-Rung Orthopair Fuzzy numbers. It can be used as a powerful tool for uncertain decision-making, which can effectively improve the accuracy and reliability of the decision-making results, and has a notable application prospect for the fields of information decision-making, risk assessment, diagnosis and so on. In this paper, firstly, the definition of LqROFZN and its operational rules are given, a new distance measure and the concept of entropy are given under LqROFZN, and the entropy of LqROFZN can assess the credibility situation of LqROFZN. Next, two aggregation operators under LqROFZN are given, namely the Linguistic q-Rung Orthopair fuzzy Z-number weighted aggregation (LqROFZWA) operator and the Linguistic q-Rung Orthopair fuzzy Z-number weighted Geometric aggregation (LqROFZWGA) operator. Finally, the MCDM method under LqROFZN is given and the credibility of the evaluation results is assessed using the entropy of LqROFZN. In a set of actual airline aircraft selection cases, the feasibility and advantages of the proposed method are verified through comparative analysis with other methods. [ABSTRACT FROM AUTHOR]

To address the situation where the multi-criteria decision making (MCDM) has problems with hesitant fuzzy preference relations (HFPRs), this paper develops a group decision making method considering the additive consistency and consensus simultaneously. First, a new normalized method for HFPRs is developed to address the situation where the evaluation information has different number of elements. Second, for improving the unacceptable consistent HFPRs, an algorithm is designed to derive acceptable consistent HFPRs. The main characteristic of the design algorithm is that the values that need to be revised are identified first, and then design the local adjustment process. Third, an algorithm is developed to obtain a group of normalized HFPRs (NHFPRs), considering the additive consistency of HFPRs. Fourth, for improving the individual consistency and group consensus simultaneously, an algorithm is designed to obtain a group of HFPRs with acceptable consistency and consensus. Finally, the method of determining the decision makers' weights and a procedure for MCDM problems with HFPRs are given. An illustrative example in conjunction with comparative analysis is used to demonstrate the proposed method which is feasible and efficient for practical MCDM problems. [ABSTRACT FROM AUTHOR]

The MCDM problem is very important and often encountered in life and in engineering as it is used to determine the best solution among various possible alternatives. In this paper, the results of the MCDM problem in the dressing process for internal grinding are presented. To perform this work, an experiment with six input parameters, including the depth and the time of fine dressing, the depth and the time of coarse dressing, non-feeding dressing, and dressing feed rate, was conducted. The experiment was designed according to the Taguchi method with the use of L16 orthogonal arrays. In addition, TOPSIS, MARCOS, EAMR and MAIRCA methods were selected for the MCDM to obtain the minimum SR and the maximum MRR simultaneously. In addition, the weight determination for criteria was implemented by MEREC and entropy methods. From the results, the best solution to the multi-criteria problem for the dressing process in internal grinding has been proposed. [ABSTRACT FROM AUTHOR]

In the context of sustainable development, building energy conservation has become the development trend of the construction industry. The selection of energy-saving building program, as a multi-criteria decision-making (MCDM) problem, has a direct influence on the actual energy-saving effect. In this paper, an integrated MCDM method combining the extended best worst method (BWM) and Weighted Aggregated Sum Product Assessment (WASPAS) method is proposed to solve the energy-saving building program selection problem under the linguistic Pythagorean fuzzy environment. The Linguistic Pythagorean fuzzy sets (LPFSs) are used to model the uncertain evaluation information of experts. The extended BWM is developed to determine the weights of criteria, while the extended WASPAS method is proposed to determine the ranking of alternatives. To validate the applicability and reliability of the proposed method, this paper presents a numerical example of the selection problem for energy-saving building programs. Some managerial insights are also given for practitioners to use the proposed method [ABSTRACT FROM AUTHOR]

The digitalization of industries is at the heart of today's global economy. However, there seems to be confusion about the most effective methods for initiating this transformation, and even more so for the manufacturing Small and Medium-sized Enterprise (SME). In a context of labor shortages, globalization and access to goods, services and skills everywhere and at any time thanks to the Internet, the need to stand out from the competition becomes a crucial issue. This research attempts to evaluate and identify the most effective ways to facilitate the digitalization in a context of manufacturing SMEs. Thanks to the measure of the digital performance and an 80-hour experience-based methodology using a questionnaire and field interviews, the determining factors of influence of the digital transformation could be raised. This paper uses a model of digital performance and hypothesis testing to try to identify the business practices and the 4.0 technologies that have the greatest effect on the performance of manufacturing SMEs. The results then intents to guide the efforts both in academia and in the field concerning digitalization of SMEs. [ABSTRACT FROM AUTHOR]

The Analytic Hierarchy Process (hereafter AHP) is a popular multi-criteria decision-making technique. The extant AHP literature usually depicts the geometric mean or the arithmetic mean as a measure of aggregation to process group decisions. However, both these measures are subject to the influence of extreme opinions, and aggregations based on them may not accurately portray the true group preference. In this paper, we propose the Common Priority Vector Procedure, which accentuates the majority group preference and diminishes the influence of extreme individual opinions. The method has been further extended to deal with multi-actor, multi-criteria and multi-group decisions. The development of Common Priority Vector Procedure, presented here, has been motivated by a real case study presented towards the end of the paper. [ABSTRACT FROM AUTHOR]

Unbalanced bidding is a serious problem in the competitive bidding practices of construction projects. Identification and prevention of unbalanced bidding is an important and complexity task for owners. This paper aims to propose an identification model of unbalanced bidding from multi-criteria decision making (MCDM) perspective. The VIKOR method is employed to detect unbalanced bidding, in which the line items and bidders are considered as criteria and alternatives in MCDM, respectively. And the engineer's estimated price is chosen as evaluation benchmarking. Then relative distances between engineer's estimated price and each bidding unit price are calculated to build decision matrix. The weights of factors are determined using entropy weight method. To illustrate the effectiveness of the proposed model, an application example is tested in detecting unbalanced bidding. Finally, the sensitivity analysis about VIKOR method is given. It shows that the presented model would provide a robust decision making support for owner in identifying unbalanced bidding. [ABSTRACT FROM AUTHOR]

The supplier selection and order allocation are two key strategic decisions in purchasing problem. The review presented in this paper focuses on the supplier selection problems (SSP) and order allocation from year 2000 to 2017 in which a new structure and classification of the existing research streams and the different MCDM methods and mathematical models used for SSP will be presented. The review was examined in three aspects: the summaries of the existing evidence concerning the problems, the identification of gaps in the current research to help determine where further investigation might be needed and positioning new research activities. [ABSTRACT FROM AUTHOR]

The upcoming packaging material trend is bio-polymeric materials since it has shown tremendous potential in practical scenarios. Even though there have been experiments performed regarding material developments, there is still no confirmation about how uncertain the developments will be. A few statistical approaches were carried out in this work to identify the role of biopolymers as a packaging material based on their thermo-mechanical and physical properties and potential compared to other packaging materials. To determine the potential of biopolymer, it is compared with other package materials currently in demand. There are three main steps in the research. The first stage is an analysis of selected different packaging materials based on Multi-criteria decision making (MCDM) technique. The material properties are analysed through the criteria of TOPSIS analysis. The ideal and negative ideal alternatives have been identified. Biopolymers have an outcome as the final best alternative among others. To confirm the TOPSIS results and its uncertainties, a sensitivity analysis is performed. This sensitivity analysis was performed in two phases. The first step is a regression analysis of the weighted parameters and input variables of the TOPSIS scheme. The second step is the variation of weights in a unitary variation ratio to identify the order of the TOPSIS results at each variation. Finally, all the results have concluded that the research intention has been fulfilled by performing TOPSIS and the sensitivity analysis has also confirmed this decision. [ABSTRACT FROM AUTHOR]

Multi-criteria decision making (MCDM) is used to determine the best alternative among various options. It is of great importance as it hugely affects the efficiency of activities in life, management, business, and engineering. This paper presents the results of a multi-criteria decision-making study when using powder-mixed electrical discharge machining (PMEDM) of cylindrically shaped parts in 90CrSi tool steel. In this study, powder concentration, pulse duration, pulse off time, pulse current, and host voltage were selected as the input process parameters. Moreover, the Taguchi method was used for the experimental design. To simultaneously ensure minimum surface roughness (RS) and maximum material-removal speed (MRS) and to implement multi-criteria decision making, MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and MAIRCA (Multi-Attributive Ideal–Real Comparative Analysis) methods were applied. Additionally, the weight calculation for the criteria was calculated using the MEREC (Method based on the Removal Effects of Criteria) method. From the results, the best alternative for the multi-criteria problem with PMEDM cylindrically shaped parts was proposed. [ABSTRACT FROM AUTHOR]

Over the last twenty years, patient opinions of the received healthcare services have emerged as a crucial quality indicator and a valuable instrument for evaluating the service quality of health organizations. However, many surveyors still utilized uncertain information for conducting this evaluation process. Whereas, in the past few years, the issues of inconsistency, indeterminacy, and uncertainty in data have been growing and have become a matter of concern in dealing with decision-making issues. This paper proposes an improved RAFSI method based on a single-valued trapezoidal neutrosophic number (SVTraNN) as a multi-attribute framework for dealing with a healthcare service quality evaluation. The proposed framework consists of two features: a feature for determining numerical criteria weights involving the procedures of the Ordinal Priority Approach (OPA) and a feature for selecting the best polyclinic through contributing our new SVTraNN Harmonic and arithmetic mean to yield criterion functions in the RAFSI method. This paper then compares the results obtained by the proposed method with other SVTraNN decision-making methods. A comparative analysis and rank reversal testing of the improved method demonstrated that the multi-attribute framework proffers the option of capability and stability in overcoming inconsistency, indeterminacy, and uncertainty information efficiently during the healthcare service quality evaluation. [ABSTRACT FROM AUTHOR]

The efficiency of cutting machining methods is generally evaluated through many parameters such as surface roughness, material removal rate, cutting force, etc. A machining process is considered highly efficient when it meets the requirements for these parameters, such as ensuring small surface roughness, high material removal rate, or small cutting force, etc. However, for each specific machining condition, sometimes the objective functions give contradictory requirements. In this case, it is necessary to implement multi-criteria decision making, i.e., make a decision to ensure harmonization of all required objectives. In this paper, a multi-criteria decision-making study is presented for three common machining methods: milling, grinding, and turning. In each machining method, the weights of the criteria were determined by four different methods, including Equal weight, ROC weight, RS weight and Entropy weight. The MARCOS method was applied for multi-criteria decision making. The best alternative was found to be the same as the weights were determined using the Equal weight and Entropy weight methods. In the remaining two weighting methods, the best alternative found depends on the order where the criteria were arranged, not these methods themselves. Direction for further research has been suggested in this study as well. [ABSTRACT FROM AUTHOR]

The performance of a piezoelectric actuator for active noise cancellation depends primarily on the quality of the actuator material and its design approach, i.e., single-layer or multi-layer actuators, stacks, benders, or amplified actuators. In this paper, material selection and multiphysics modeling were performed to develop an optimal piezoelectric plate actuator for active noise cancellation. The material selection process was analyzed using two multi-criteria decision making (MCDM) approaches for material selection, i.e., figure of merit (FOM) for actuators and the technique for order of performance by similarity to ideal solution (TOPSIS). Of the 12 state-of-the-art piezoelectric actuator materials considered in this article, PMN–28% PT is the best material according to TOPSIS analysis, while P b I n 1 2 N b 1 2 O 3 24 % − P b M g 1 3 N b 1 3 O 3 − P b T i O 3 (PIN24%-PMN-PT) is the best material according to FOM analysis. The ranking of state-of-the-art piezoelectric material categories for actuators according to the two analysis is consistent and the category of monocrystalline piezoelectric materials has the highest actuation performance. The multiphysics modeling was performed using ANSYS Mechanical using two different approaches: one using Ansys Parametric Design Language (APDL) command fragments, the other installing the PiezoAndMEMS ACT extension in ANSYS. Static structure, modal, and harmonic response analyses were performed to determine an optimal pair of piezoelectric plates to be used as an actuator for active noise cancellation. A pair of plates of the same materials, but of different dimensions turns out to be the optimal piezoelectric plate actuator for active noise reduction, according to the two multiphysics modeling methods. [ABSTRACT FROM AUTHOR]

The paper explores the potential impact of social enterprises on social exclusion. In particular, the role of social enterprises in labour market integration of socially excluded individuals is analysed within the existing theoretical and policy discourses of exclusion. Taking into account the difficulties in measuring the social impact of social enterprises, our study contributes to the quantitative literature on the performance of social enterprises, taking the number of integrated people as a measure of the impact on social exclusion. The research is based on data on the employment of marginalized groups, derived from a unique dataset collected by a recently conducted survey of social enterprises in Serbia. The original methodological framework combines statistical methods and multi-criteria decision making model, in order to evaluate the contribution of different types of enterprises to the employment of excluded individuals. Weights determination for the MCDM model is performed using entropy while TOPSIS method is applied for the ranking of the types of social enterprises according to the employment of socially excluded categories. The results indicate that enterprises for employment of persons with disabilities, citizens' associations and cooperatives in Serbia contribute the most in integrating the socially excluded. [ABSTRACT FROM AUTHOR]

Health-care waste (HCW) management is an important issue, especially in developing countries. How to choose the best management technology is a challenging and open subject in this issue. Limited work has been done, but there is still a lack of a technical approach that not only takes into account multi-granular linguistic terminology, but also considers the attitude characters of decision makers (DMs). To adress the above problem, in this paper a hybrid multi-criteria decision making scheme is proposed based on soft likelihood function and D-numbers. First, the D-numbers is used to characterize complex multi-grained decision information. Secondly, a novel soft likelihood function based on power ordered weighted averaging operator (POWA) is designed to effectively take into account the DMs' preferences, which is then integrated into the proposed HCW management approach. Eventually, the effectiveness and superiority of the proposed approach is demonstrated through an application example. In particular, an intuitive advantage has been confirmed that the proposed method can adjust the gap between adjacent alternatives through decision preference to distinguish differences. This is expected to provide a reliable fault-tolerant interval for decision-making in HCW management, and further improve the reliability of the algorithm. In addition, the analysis and evaluation also confirm the reliability and practicality of the proposed technology. [ABSTRACT FROM AUTHOR]

• Conservation priority areas (CPAs) was established by balancing ecosystem services. • Multi-criteria based CPAs selection was reliably verified by using single strategies. • In the CPAs, 4 services can achieve high conservation efficiencies simultaneously. • Under the workflow of the study, the proportion of biodiversity can be improved. • Various vegetation should be taken into account for future ecological management. Facing rapid ecological degradation in the Qinghai Tibet Plateau (QTP), the determination of priority areas for conservation (CPAs) based on ecosystem services (ESs) is a key step for nature conservation and sustainable development. However, the trade-off between services makes the plan of maintaining protected areas (PAs) a challenge. In this study, by quantifying a variety of essential ESs in the QTP from 2000 to 2015, we used the multi-criteria ordered weighted average method to balance the trade-offs and determine the key CPAs for ES conservation. We found that the multi-criteria based selection of CPAs leads to higher (1.35) and more balanced ES protection efficiency (PE) than the single strategy. The CPAs obtained based on the logical framework of this paper are mainly located in the southeastern QTP and cover an area of 12.78 % of the QTP (330,124.76 km2). The comprehensive PE of ES was 1.68, and the PE of carbon storage, water yield, soil conservation, and cultural service were 2.20, 2.17, 4.54, and 1.59, respectively. Additionally, compared with the existing PA settings, our results can increase the proportion of biodiversity of amphibians and birds by more than 12 %. The framework of CPAs selection in this paper can provide a reference for the government's growing nature conservation affairs, which will contribute to sustainable development. [ABSTRACT FROM AUTHOR]

Smart cities are included in the literature as a technology-based concept that has been on the agenda in recent years and whose framework is constantly changing with the changes in technology. There are different frameworks and indexes to define the smartness of a city. Smart City Index 2021 published by Institute for Management Development (IMD) and Singapore University of Technology and Design (SUTD) is one of the accepted studies in the world. In the report of Smart City Index 2021, 118 cities are evaluated in five criteria namely health & safety, mobility, activities, opportunities (work & school) and governance. To re-evaluate the cities and compare the results, a Multi-Criteria Decision Making (MCDM) process including Entropy based Complex Proportional Assessment (COPRAS) and Addivite Ratio Assessment (ARAS) methodology is applied in this paper. To prioritize the criteria, entropy weight method is used. 118 cities are ranked both technologically and structurally using the COPRAS and ARAS method. As a result of the analyses, according to these methods, the rankings of the smart cities are the same. Also, when technologically smart cities are listed, it is determined that the first three countries are Zhuhai, Shenzhen, Nanjing, and at the same time, Abu Dhabi, Chongqing, Hangzhou in terms of structurally. [ABSTRACT FROM AUTHOR]

Background: During major maintenance projects on offshore installations, flotels are often used to accommodate the personnel. A gangway connects the flotel to the installation. If the offshore conditions are unfavorable, the responsible operatives need to decide whether to lift (disconnect) the gangway from the installation. If this is not done, there is a risk that an uncontrolled autolift (disconnection) occurs, causing harm to personnel and equipment. Objectives: We present a decision support model, developed using the DEXi tool for multi-criteria decision making, which produces advice on whether to disconnect/connect the gangway from/to the installation. Moreover, we report on our development method and experiences from the process, including the efforts invested. An evaluation of the resulting model is also offered, primarily based on feedback from a small group of offshore operatives and domain experts representing the end user target group. Methods/Approach: The decision support model was developed systematically in four steps: establish context, develop the model, tune the model, and collect feedback on the model. Results: The results indicate that the decision support model provides advice that corresponds with expert expectations, captures all aspects that are important for the assessment, is comprehensible to domain experts, and that the expected benefit justifies the effort for developing the model. Conclusions: We find the results promising, and believe that the approach can be fruitful in a wider range of risk-based decision support scenarios. Moreover, this paper can help other decision support developers decide whether a similar approach can suit them. [ABSTRACT FROM AUTHOR]

This paper deals with the hesitancy in decision making. Since the decision makers generally doubt to evaluate the alternatives and the criteria in hesitant situations, the existing methods do not satisfy them. Therefore, hesitant versions of Fuzzy-AHP (HF-AHP) and Fuzzy Axiomatic Design (HF-AD) are introduced in this paper. HF-AHP lets the decision makers to use hesitant fuzzy linguistic terms while performing the pairwise comparisons when they are indecisive. HF-AD is used to define the system and design ranges of the items in a hesitant situation. In addition, a case study is revealed as a numerical example in which the best supplier is selected among six alternatives regarding five criteria. In that case study, both weighted and unweighted versions of HF-AD are used. In the weighted version, HF-AHP is used to determine the weights of the criteria. Furthermore, sensitivity analysis is performed to check the robustness of the decision. Moreover, these proposed techniques are compared with non-hesitant versions. According to the results, the decision makers feel more confident with the hesitant versions. Hence, the primary contributions of this study are to develop HF-AD and HF-AHP which are helpful for the decision makers to express their preferences in hesitant situations. [ABSTRACT FROM AUTHOR]

In this paper is researched how to achieve an effective fleet maintenance planning in transport companies, which contributes in increasing the fleet energy efficiency and in achieving the companies 'goal. Within the fleet maintenance planning, managers have to make the right decisions on the selection of vehicle service centers in the region where the maintenance work will be realized. The mentioned decision is affected by a number of different interdependent factors (criteria). Based on a survey, relevant factors (criteria) were defined. As defined factors are interdependent and differently influence the mentioned decision, an approach of decision making trial and evaluation laboratory (DEMATEL)-based analytic network process calledDANP was applied. In this respect, authors propose a hybrid multi-criteria decision making model. The proposed model was applied in the companies to demonstrate how effective their managers are in the maintenance planning and how this effectiveness influences the fleet energy efficiency and fulfilment of companies' goal. [ABSTRACT FROM AUTHOR]

This paper designs a bidding and supplier evaluation model focused on strategic product procurement, and develops their respective evaluation knowledge bases. The model is built using the most relevant variables cited in the reviewed procurement literature and allows to compare two evaluation methods: a factor weighting method (WM) and a fuzzy inference system (FIS). By consulting an expert panel and using a two-tuples symbolic translation system, strong fuzzy partitions for all model variables are built. The method, based on central symmetry, permits to obtain the fuzzy label borders from their cores, which have been previously agreed among experts. The system also allows to agree the fuzzy rules to embed in the FIS. The results show the FIS method's superiority as it allows to better manage the non-linear behavior and the uncertainty inherent to the supplier evaluation process. [ABSTRACT FROM AUTHOR]