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Increasing energy prices and market volatilities force energy intensive industries to implement energy management systems in order to ensure competitiveness. In this paper, we focus on the strategic level of energy management, specifically, on the analysis of the internal and external conditions that form the basis for strategic development. For this, we selected the case of the Austrian paper and pulp industry. We applied a hybrid method by combining an analysis of strengths, weaknesses, opportunities and threats with an analytic hierarchy process which was based on a survey of expert opinion. The results show that cost-related factors predominate. According to our analysis, the four most important factors are all directly linked to energy costs, energy efficiency, and the energy market. Experts pay little attention to environmental issues or to energy market volatilities. Apart from that, the combination of an analysis of strengths, weaknesses, opportunities and threats with an analytic hierarchy process promises to be a valuable tool for strategic energy management. This is especially true for energy intensive companies and/or sectors, since it enables decision makers to take strategic decisions based on a systematic understanding of the main issues. [ABSTRACT FROM AUTHOR]

• Proposed a method for multi-axis random vibration topology optimization. • Enhancing vibration resistance and extending life during the topology phase. • Prompting the structure to add load-bearing paths to resist random vibration loads. • Guiding the topology towards forming a vibration-resistant structure. • Expanding HCA into the field of random vibration performance topology optimization. Considering the lack of effective solutions for multi-axis random vibration topology optimization problems, and recognizing that multi-axis random vibration excitation is the most common loading conditions experienced by structures during their operational life, this paper proposes a multi-objective topology optimization method for multi-axis random vibration. By combining Hybrid Cellular Automata (HCA) and Analytic Hierarchy Process (AHP), this method aims to enhance the vibration resistance of structures and extend their fatigue life during the topology optimization phase. To validate the effectiveness and engineering practicality of this method, two engineering cases were designed: a cantilever beam case and an automotive steering knuckle case. Multi-objective topology optimization were conducted with objectives including mass, stiffness, and vibration intensity metric (root-mean-square stress). The two cases demonstrate that the control group's topology model exhibits weaker resistance to random vibrations and shorter fatigue life. In contrast, the validation group's topology model introduces an additional load path near the excitation point, effectively dissipating the impact of vibration excitation. This enhances the structure's vibration resistance and significantly extends its fatigue life. [ABSTRACT FROM AUTHOR]

Geospatial techniques are useful to understand the groundwater resources assessment, development, and management. Groundwater mapping is essential to counter the excessive withdrawal of groundwater and fulfil the need of drinking, irrigation water in hard rock areas. Currently, the main problem is facing the groundwater level is decreasing due to less rainfall, climate changes and increasing demand, which is under in the hot zones. This results can be more useful for future challenges, sustainable development and demand to Jakham river basin. The main objective of this paper to demarcated the groundwater potential zones (GWPZ) using geospatial techniques for the hard rock region with the reference of aquifer parameters. In this paper, we have used to total eight thematic layers such as geomorphology, land use, soil, topographic elevation, slope, post-monsoon groundwater level (GWL), net recharge, and transmissivity, which are prepared from satellite data and field verification. All thematic layers were integrated for assigning the weights to demarcation of the groundwater potential zones in the RS and GIS environment. The selected thematic layers and features were assigned weightage and normalized by the analytic hierarchy process (AHP) technique. Finally, the thematic layers were systematically integrated using weighted overlay analysis within a GIS environment. We have classified into five GWPZ classes i.e. very high, high, moderate, low, and very low for basin area using GIS, and AHP methods. The study area result indicated that high and moderate zone, which is confined in the central part of the basin, covers 2.43 % and 43.88 % area, respectively. The low (49.21 %) and very low (4.25%) GW potential zone is under the confined aquifer in the high slope and rock outcrops formations near the basin boundary. The final GWPZ map was validated with groundwater level fluctuation data, which illustrates the accuracy of the adopted approach. This unique approach and conclusions of this work may also help to develop the framework and policies for swiftly analyzing groundwater recharge planning, development and locating the artificial recharge structures in the other semi-arid, arid and hard rock regions. [ABSTRACT FROM AUTHOR]

Machine Learning as a Service, MLaaS refers to cloud-based platforms that provide machine learning tools and infrastructure to users, allowing them to access and utilize machine learning capabilities without managing the underlying hardware and software. Cloud service providers offer scalable and flexible resources, enabling businesses to train and deploy machine learning models efficiently and cost-effectively. Multi-Criteria Decision making, MCDM helps individuals or organizations make choices when multiple criteria or objectives are involved. It aims to find the best alternative among a set of available options by considering various criteria or factors that are relevant to the decision. Machine learning as a service (MLaaS) and MCDM are two distinct concepts that can be combined to create powerful decision-making solutions. The present paper proposed an integrated approach based on the Analytic Hierarchy Process and TOPSIS method for choosing the best MLaaS cloud. Four alternatives for MLaaS cloud were analyzed based on seventeen shortlisted criteria. Based on the calculations, conclusions have been reached and potential study areas have been identified. [ABSTRACT FROM AUTHOR]

• A new simulation methodology, intended bounded rationality methodology, is proposed. • Evaluation cost-benefit of different aspects of decision support techniques. • Classification of errors that a decision support technique can generate is proposed. • Consistent erroneous judgments and inconsistent correct judgments are possible. • A case where consistency condition in AHP provides maximum 5% of the expected return. Expert's judgments have been crucial in the development of decision theory; however, what criterion to use in the selection of experts remains an issue to address. Decision support techniques proposed to improve the quality of expert judgment decision making consider a demonstrated inconsistency of the judgments expressed by an expert as a criterion of exclusion in the decision-making process of such expert. Although consistency appears to be a desirable condition to qualify as "expert", little is known about the quality of the decisions made imposing consistency as the expert qualifying condition. This paper proposes a simulation methodology, based on an automaton programmed to make decisions in an intended but bounded rational way, to assess the cost-benefit of different aspects of decision support techniques. Within this methodology, the imposition of the consistency condition in the selection of experts is studied. In particular, the paper shows with a case study example that the Analytical hierarchy process (AHP) decision support technique expected payoff is at most 5% higher when implementing Saaty's consistency criterion of the expert's judgments than when the consistency criterion is not considered. [ABSTRACT FROM AUTHOR]

This paper presents a variation of the classical Diet Problem, in which a Linear Programming model is applied in order to minimize meal costs while meeting the nutritional needs of the individual. With a hybrid application of the method Analytic Hierarchy Process (AHP) – by using the software Three Decision Methods (3DM) – and a Linear Programming (LP) model, the objective of this work was to ensure that 4 previously defined meals were chosen, out of a total of 7, to be part of the menu of a Brazilian company that provides lunch to its employees. With the AHP Method it was possible to determine the preference of employees for each meal, according to a series of criteria, and define a ranking with scores for each one of them. Using these scores, a Linear Programming model was created whose objective-function was to maximize employee satisfaction with the selected meals, while meeting the maximum cost constraint assigned to this selection. The PL model returned a satisfactory result, in which, counterintuitively, not the 4 meals with the highest score in the application of the AHP method – to maximize satisfaction – nor the 4 cheapest meals – to respect the cost limit – were selected, but a combination of these two characteristics. The methodology proposed in this paper can be applied for the most diverse problems of the public, private or military sectors. [ABSTRACT FROM AUTHOR]

• Evaluating the Water Resources Constraint Intensity(WRCI) from the Perspective of High-quality Development. • An Analytic Hierarchy Process (AHP) model reformed by entropy technology and a multi objective fuzzy membership function were employed for indicator aggregation. • The spatiotemporal changes and correlation of UQDI, WRI, and WRCI in 78 prefecture level cities in the Yellow River Basin during 2011–2020 were analyzed. Promoting the high-quality development of urbanization is a crucial way to achieve sustainable development goals. Water resources are a rigid constraint for such development. However, There is still room for improvement in the research on the spatio-temporal pattern and key driving factors of high-quality urbanization development under the constraint of water resources. Aiming at the problem that the high-quality development of urbanization in the Yellow River Basin (YRB) is facing water resources constraints, this paper discussed the spatial–temporal pattern and key drivers of the high-quality development of urbanization in the YRB under water resource constraints by using the Analytic Hierarchy Process model reformed by entropy technology, multi-objective fuzzy membership function, spatial autocorrelation analysis and obstacle model. The results revealed that, first, we found the High-Quality Urbanization Development Index (UQDI) exhibited steady growth, while both the Water Resources Index (WRI) and the Water Resources Constraint Intensity (WRCI) initially increased and then decreased during the study period. Second, the UQDI displayed a dual-core pattern, with the Shandong Peninsula urban agglomeration and the Central Plains urban agglomeration serving as the cores. WRI exhibited relatively stable spatial distribution, with the southeast region outperforming the northwest. WRCI also demonstrated a relatively stable spatial distribution, resulting in two weak-constraint areas, represented by Shandong and Henan, and a strong-constraint area centered around Ningxia. Third, the UQDI, WRI, and WRCI exhibited spatial interdependence. The spatial interdependence of UQDI and WRI increased, while that of WRCI decreased during the study period. The three indexes also displayed a clear pattern of local clustering in space. Two low-value aggregation areas, namely Shandong and Henan, and a high-value aggregation area located in Ningxia, emerged during the study period. Last, the WRCI was primarily influenced by the fundamental conditions of water resources. The main influencing factors included per capita water resources, mean annual precipitation, total water resources, water resources modulus, and the total amount of foreign investment utilization. In light of the research findings, the paper proposes policy recommendations for promoting high-quality urbanization development in the YRB. This study provides decision-making guidance for countries and regions in arid areas to solve the water resources constraints on the high-quality development of urbanization. [ABSTRACT FROM AUTHOR]

With the evolution of Industry 4.0, the most advanced technologies have been invented and due to rapid globalisation, supply chains (SC) have become vulnerable to various risks. Risk management performs a key role in operating SC effectively in variety of uncertain circumstances. This paper aims to reveal the adaptability of digital technologies in supply chain networks, identify and analyse the various emerging supply chain risks in the industry 4.0 environment, and develop a framework to mitigate the risk level. A systematic literature review was conducted to identify and analyse the emerging supply chain risks, and Analytical Hierarchy Process (AHP) method was used to develop a conceptual risk mitigation framework. The contribution of this study lies in the taxonomy study, and findings revealed that digitalisation of supply chain design for risk mitigation shed light on future research. Additionally, it focuses on the potential to enhance supply networks' efficiency and responsiveness. [ABSTRACT FROM AUTHOR]

Decision analysis is a key aspect in improving slums intervention strategies utilizing a variety of tools to evaluate all relevant information that support decision-making process for dealing with the complexity of slums interventions policies. This paper presents a framework integrating Multi Criterion Decision Analysis (MCDA) with (GIS) based decision support tool to quantitatively assess land suitability for site relocation of an urban slum site utilizing Analytical Hierarchy Process (AHP), which is commonly used for fastest growing decision-analytic techniques in several disciplines for the determination of various aspects weights. Herein Batn Al Baqara region (which is located in south of Cairo) was selected as study area to be relocated as it was considered among the most difficult to deal with, three proposed relocation sites were selected and analyzed using MCDA-GIS Model. Twelve different criteria were utilized to evaluate the degree of suitability of the relocation sites. A five degree of suitability were employed according to the different criteria scores for each site. The results supported that Al Asmarat is the most suitable site for the relocation of slum since it achieved the highest evaluation score (84.92 %) when the model was applied to the relocation sites. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid fuzzy AHP (Analytic Hierarchy Process) – DEMATEL (Decision Making Trial and Evaluation Laboratory) approach to determine the most relevant criteria to measure the performance of municipal Emergency Medical Service (EMS) providers transparently and comprehensively. Allocation of emergency medical services affects public finances and the district's social management. Therefore, evaluating EMS providers' performance is crucial based on multiple factors, such as equipment, vehicle condition, pre-hospital care, diagnoses, costs, staff training, and financial stability. Multi-criteria decision-making tools can help to obtain a comprehensive and objective assessment of EMS providers' performance rather than relying solely on response time, which can be subject to random fluctuations. The proposed approach uses a hybrid fuzzy AHP-DEMATEL that determines that the managerial criteria are more relevant in the process, weighing 47.4%. This model will help ensure the quality and transparency of emergency medical services and guarantee that resource allocation is accountable. This will solve the district's current challenge when deciding whom to assign the EMS concessions. The results of this study demonstrate the significance of using a comprehensive evaluation model to ensure the quality of emergency medical services and enhance the decision-making process of state authorities. [ABSTRACT FROM AUTHOR]

There are different studies has introduced different methods and techniques to improve the performance and to reduce the delays in delivering construction projects. The selection of qualified contractors has a crucial importance which ensures delivering projects within the required time, quality, and cost. There are different national classification systems for contractors which are based on some similar and different criteria. This paper aims to develop a new model that helps in evaluating contractors in pre-tendering stage. The establishment of this model starts by listing 39 different criteria that are extracted from previous related studies. Then, 9 experts conducted a pairwise comparisons of those criteria using Analytical Hierarchy Process (AHP) which resulted in 10 important criteria that should be used in evaluating construction contractors in pre-tendering stage. Those 10 criteria were then evaluated by 21 specialized mangers in different contract departments to get the weight of each criterion using Multi Attribute Utility Theory (MAUT) which converts those different criteria that have different attributes dimensions to one unified measurement scale identified as the multi-attribute "utility". At the end, the selection criteria are evaluated using numerical and nominal scale to calculate the final score using the weights of those criteria which will allocate the contractors that can go to the tendering stage. As this model introduces a method for evaluating contractors before tendering stage, it also allows the clients or owners redefine the selection criteria and to decide the minimum result to allow contractors to move to the tendering stage. So, this model will help decision makers to ensure that the contractor's characteristics and capabilities meet the requirements of the allocated project. Effective and objective qualification processes will serve both parties, owners, and contractors, in delivering construction projects. The criteria of this model are established based on the requirements of the construction industry in Saudi Arabia. [ABSTRACT FROM AUTHOR]

This paper considers the problem of selecting a state-made electronic document management system (EDMS) using the analytic hierarchy process (AHP) model. The problem of EDMS selection from two available variants is analysed and the selection criteria related are highlighted on the basis of the literature and the authors' experience. Calculations related to pairwise comparisons and prioritisation between criteria and variants form the core of the paper. This problem is only applicable to municipalities in Poland that have implemented an older state-made system; based on pair-wise comparisons, retaining the older system is preferable to implementing the new state-made EDMS because of the lack of integration of the new EDMS with internal systems. [ABSTRACT FROM AUTHOR]

Hadoop is an open-source framework that is widely used to store and process large amounts of data. Its core component is called YARN that is responsible for resource management and job scheduling for Big Data applications. Although YARN has very advanced processing performance. It suffers from resource allocation problems when used in a heterogeneous cluster serving multiple users. To deal with this heterogeneity and overcome the degradation of cluster, load balancing has become a major challenge for Hadoop run-time management. In this paper, an efficient resource allocation strategy combining multi-criteria decision-making and accurate clustering of nodes in a heterogeneous Hadoop environment is proposed. A multi-criteria decision approach relying on a modified analytical hierarchy process method is applied to assign a score to jobs depending on the resources requirements at run time. First, the proposed system profiles the available nodes by grouping them into clusters with similar performance. Second, the system performs a dynamic multi-criteria selection on resource requests by assigning scores to jobs according to their resource usage. Third, node groups and job scores are used to dynamically allocate jobs to the most appropriate resources in real time while keeping load balance in the heterogeneous cluster. The aims of this present paper are to optimize the resource utilization and achieve a high performance of the Yarn resource management by considering a heterogeneous environment. The experimental results demonstrate that the proposed algorithm provides the best utilization of available resources by 45% and 12% compared to fair and H-fair respectively, which implies a minimum job execution time in a heterogeneous cluster. [ABSTRACT FROM AUTHOR]

The research uniquely focuses on advancing the field of fuzzy sets, specifically proposing a novel approach using Hexagonal Type-2 Fuzzy Variable (HT2FV), to handle higher degrees of uncertainty. Flooding, a recurrent and impactful phenomenon, necessitates a robust approach to effective disaster management. The study delves into the humanitarian supply chain dynamics during movement crises and flood catastrophes, introducing a novel methodology to harness the potential of HT2FV. Central to the paper is the innovative defuzzification concept of Critical Value (CV) reduction, strategically employed to eliminate fuzzy components within HT2FV, transforming it into crisp data. The research extends its novelty by proposing a comprehensive approach to distributing relief materials, employing a Multi-objective, Multi-level, Multi-modal (MOMLMM) approach, with a primary focus on boats for inundated areas. Significantly, the study aims to optimize the allocation of resources, minimize time and cost under uncertain environments, and enhance disaster relief operations. The paper is the first to use new hexagonal fuzzy numbers (HFNs) and focuses on how they can be used to sort vulnerable areas using the fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods of the Multi-Criteria Decision-Making (MCDM) process. A case study of the 2022 Assam flood is looked at and solved using the Weighted Sum (WS), Neutrosophic Compromise (NC), and Goal Programming (GP) systematically on the LINGO solver to see if the suggested method can be used. Further, sensitivity analysis is employed to establish optimal credibility levels to validate the proposed methods. A real-life case study lends practicality, substantiating the approach's efficacy. At the same time, comprehensive comparative analysis compares and contrasts findings from different studies to synthesize existing knowledge and identify future scope, contributing significantly to the field of fuzzy sets. [ABSTRACT FROM AUTHOR]

The full utilization of solar energy resources along the road is an effective method to solve the energy shortage in transportation. The key to this is an accurate evaluation of solar energy resources, which provides the rationale for the optimal location of road photovoltaic (PV) projects. However, determining the availability of solar energy resources in road areas before route corridor planning remains difficult. To address the issue, this paper developed a standardized method. Firstly, this paper analyzed the critical factors affecting the availability of solar energy resources. They were meteorology, topography, land use type, geology, and location. On that basis, we developed a four-level evaluation indicator system. Then, it proposed a multi-indicator evaluation method based on the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). It used AHP to calculate the weights of each indicator, with solar radiation being the most important. It used GIS to analyze and overlay the spatial distribution of multiple indicators to obtain the map of suitability grades, which could be used to route corridor selection for road PV projects. It also used a case study to demonstrate how the method is applied. The findings show that the method can accurately evaluate the availability of solar energy resources. Furthermore, it studied the appropriate division of evaluation units and it is advised that they shouldn't be larger than 30 m × 30 m. These results provide guidance as a reference for the application of road PV projects and site selection for route corridors worldwide. That will promote the integration of transportation and energy in the future. • The paper addresses the problem of solar energy resources evaluation in road areas. • The paper establishes a universal evaluation indicator system. • The paper proposes a standardized evaluation method based on AHP and GIS. • This method presents the obtained evaluation results as suitability grade map. • This method helps select route corridors with good power generation potential. [ABSTRACT FROM AUTHOR]

In every decision-making problem which involves two or more criteria, there is to identify the relative importance of those criteria in order to make a proper decision. Very often, a decision-makers employee, for this purpose, subjective weighting methods, such as Analytic Hierarchy Process (AHP) or Ranking Comparison (RANCOM). However, there is no simple way to compare the quality of the weights identification using different methods. To address this issue, this paper proposes a simple but Efficient Weights Similarity Coefficient, which allows us to evaluate the relative performance of different subjective weighting methods. Furthermore, we propose a framework that utilizes the proposed coefficient in order to provide more complete comparison results. To demonstrate the applicability and effectiveness of the proposed framework, a case study is performed to compare two popular weighting methods: AHP and RANCOM. The results of the comparison prove that proposed coefficient with the combination of the proposed framework is an Efficient instrument for weighing methods comparison. [ABSTRACT FROM AUTHOR]

Customer feedback and satisfaction are critical indicators of success in the hospitality industry. The influence of customer reviews on the decisions of other customers to visit and on the brand reputation of hotels necessitates that hotel managers conduct a thorough analysis of customer satisfaction. This paper presents an approach for assessing the overall customer satisfaction of hotels by using the Analytic Hierarchy Process (AHP) method, the SERVPERF scale, and the 2-tuple linguistic model. The five dimensions of the SERVPERF scale have been customized to assess customer satisfaction in hotels, considering various hotel aspects such as rooms, service, cleanliness, and so on. The AHP method is applied to obtain the importance of the SERVPERF scale for each aspect of the hotels. The 2-tuple linguistic model is employed to address the issue of information loss in linguistic information fusion and enhance the comprehensibility of the results for hotel managers. The functionality of this proposal has been evaluated through a case study of luxury hotels in London, using 15,511 customer reviews gathered from TripAdvisor. The results show that the proposed model effectively captures and summarizes customer satisfaction with luxury hotels in London, allowing hotel managers to identify areas for improvement and discover potential business opportunities. This ultimately helps to increase customer satisfaction. [ABSTRACT FROM AUTHOR]

Supply chain management is critical for any organization. To improve the performance of a firm's supply chain, it is important to have a freight forwarder evaluation process in place. This paper develops an analytical hierarchy process (AHP) methodology to perform a multi-criteria evaluation of freight forwarders. It analyzes different criteria that would be employed in the evaluation and selection of forwarders. The problem of choosing the best freight forwarder is evaluated in terms of quality of service, specialized service, network, competitive price, information and technology, and sustainability. A total of fourteen sub-criteria are considered including quality of service, network, information and technology, and sustainability. The study revealed that specialized service is the most important criterion with a weight of 54.3% followed by quality of service, competitive price, information and technology, network, and sustainability. Proven experience is the most important sub-criterion with overall weight of 36.2% followed by knowing the regulations with overall weight of 18.1%. Freight forwarder B is the best option with the highest weight with respect to proven experience and knows the regulations with values of 3.62 and 1.629, respectively. [ABSTRACT FROM AUTHOR]

Emerging innovative manufacturing systems combine cyber-physical systems (CPS), the Internet of Things (IoT), and data analytics to develop a framework for predictive and adaptive purposes. The fifth industrial revolution, or Industry 5.0, envisions human-machine cooperation in a mutually beneficial symbiotic relationship. Human intelligence is responsible for high decision support providing feedback to the model, and the machine is dedicated to the empirical processing that builds the model. This paper presents a human-centric framework incorporating various maintenance stakeholders' perceptions to assess the relationship between key maintenance factors affecting manufacturing sustainability. The work methodology integrates two methods: the fuzzy analytic hierarchy process (F-AHP) and the elimination and choice expressing reality (ELECTRE III). The F-AHP is used to compute the relative weights of the evaluation criteria of the maintenance factors. Then, the criteria weights will be used as the input for the ELECTRE III method to rank the maintenance factors. It was observed that the proposed approach is robust and can classify the maintenance factors according to their importance to sustainable manufacturing. [ABSTRACT FROM AUTHOR]

In pharmaceutical warehousing operations, a scientific and reasonable medicine and shelf matching strategy can improve medicine shelving efficiency and manual work efficiency. However, the traditional matching strategy has the problems of static matching and low matching efficiency, so this paper proposes the matching algorithm for drugs and shelves based on the fuzzy analytic hierarchy process and Bayesian convolutional neural network (FAHP-BCNN). First, we propose a drug-shelf matching degree model and discuss the influence of the dynamic matching process on the matching results by studying two parts: the attribute matching degree and the dynamic matching influence degree. Secondly, this paper quantitatively assessed the importance of the two matches by means of the fuzzy analytic hierarchy process. Finally, we mapped the massive matching information onto Bayesian convolutional neural network nodes, constructed a dynamic matching network model, and obtained competitive matching strategies and results. The experimental results show that the FAHP-BCNN algorithm exhibits better matching results in all three scenarios with different quantity ratios of drugs and shelf matching. Compared with the fixed cargo matching strategy of the ABC classification method, the FAHP-BCNN algorithm shows excellent performance in both the manual walking distance index and fatigue index. In summary, the drug-shelf matching algorithm based on FAHP-BCNN is effective and can provide theoretical support for pharmaceutical warehousing enterprises to perform drug-shelf matching. [ABSTRACT FROM AUTHOR]

Several methods of preference modeling, ranking, voting and multi-criteria decision-making include pairwise comparisons. It is usually simpler to compare two objects at a time, furthermore, some relations (e.g., the outcome of sports matches) are naturally known for pairs. This paper investigates and compares pairwise comparison models and the stochastic Bradley–Terry model. It is proved that they provide the same priority vectors for consistent (complete or incomplete) comparisons. For incomplete comparisons, all filling in levels are considered. Recent results identified the optimal subsets and sequences of multiplicative/additive/reciprocal pairwise comparisons for small sizes of items (up to n = 6). Simulations of this paper show that the same subsets and sequences are optimal in the case of the Bradley–Terry and the Thurstone models as well. This somehow surprising coincidence suggests the existence of a more general result. Further models of information and preference theory are subject to future investigation to identify optimal subsets of input data. • Multiplicative/additive/reciprocal pairwise comparisons vs. Bradley–Terry model. • Their equivalence is shown in case of consistency. • All filling in levels are investigated. • The same subsets of comparisons are shown to be optimal even in inconsistent cases. • Results raise new research direction: Are such coincidences valid in further models? [ABSTRACT FROM AUTHOR]

The fuzzy set theory as one of the key agents of artificial intelligence has been used to deal with vagueness and imprecision during the decision-making process. The software requirements selection is a multicriteria decision making problem which has a key importance for several software development companies. Few methods have been developed to select the software requirements from the list of the elicited requirements using fuzzy analytic hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) methods. Based on our review, we found that little attention is given on the comparison between the fuzzy AHP and fuzzy TOPSIS methods in the context of the software requirements selection problem. To address this issue, this paper presents a comparative analysis of fuzzy AHP and fuzzy TOPSIS methods by considering the small and large set of requirements of an institute examination system based on the following factors: agreement measure, time complexity, rank reversal issue, and number of judgments by decision makers. Based on the comparative study, we found that both fuzzy AHP and fuzzy TOPSIS methods produce the same set of functional requirements based on agreement measure metric in both dataset-1 and dataset-2. Fuzzy AHP requires less time to generate the ranking order in dataset-1; and fuzzy TOPSIS performs better then fuzzy AHP in dataset-2. Fuzzy AHP causes the rank reversal issue; and there is no rank reversal issue in fuzzy TOPSIS and it produces the consistent results. Fuzzy TOPSIS requires less judgment by decision makers then fuzzy AHP. Finally, we discuss the future research directions in the area of SRs selection problem. [ABSTRACT FROM AUTHOR]

In this paper, the ecological quality of Singrauli sub-district over a decade was investigated based on images of IRS LISS III and Landsat series of 2005, 2010 and 2015 respectively. The Analytic Hierarchy Process (AHP) was employed to develop the Geo-Spatial Ecological Impact Index (GEII) by assigning weights to the five ecological parameters (vegetative cover, moisture content, built-up index, water index and Land Surface Temperature (LST) and to determine the degree of impact on each one due to the increased anthropogenic activities. The study concluded that, there was an increase in the built up and the overall LST by 6.24 °C whereas, the vegetation covers and moisture content has decreased during the years 2005 to 2015. Aggregate change in ecological quality can be inferred from the increasing mean of GEII values from 3.39 to 3.61 indicates deteriorating ecological quality. The predicted map of GEII 2025 prepared using artificial neural network (ANN) revealed that the high ecological impact zones will cover 37.95% of the area by 2025. The result obtained from the study can be useful for policy and decision makers for sustainable development of urban sectors and natural resource management of the area with respect to ecological impact assessment. [ABSTRACT FROM AUTHOR]

Now that the coronavirus epidemic continues, hospitals have made a series of control measures, which makes the already relatively backward, slow traffic system around the large hospitals in the old city face more severe problems. This paper, based on the analysis of the current issues of slow traffic in large hospitals in old urban areas, according to the elements affecting slow traffic and the needs of slow traffic around hospitals, safety, accessibility, diversion, convenience, and comfortableness are used as the first level indicators, the index weights are determined by applying Analytic Hierarchy Process, and the comprehensive evaluation model of slow traffic around large hospitals in the old city is constructed by using Extentics. Through the case study, the scientific and practicality of the method is verified, which provides a scientific way for the safe and efficient operation of the slow traffic system around the large hospitals in the old city under the present epidemic control. [ABSTRACT FROM AUTHOR]

Complex environments, conflicting criteria, uncertainties, and inaccurate information are some characteristics of many nowadays real-world decision-making problems. The Multi-Criteria Decision-Making (MCDM) methodology is one of the most used, perhaps because it drives decision-making processes to be more rational, efficient, and effective. Thus, the Armed Forces of several countries have used MCDM methods in the Life Cycle Management of Defense Systems (LCM-DS) to deal with military systems' complexity, breadth, and sensitivity. However, despite the rich and vast literature available on several MCDM methods applied to LCM-DS problems, there is a lack of a recent bibliometric study on this relevant subject. This paper presents an analysis of a quantitative approach based on bibliometric metrics to evaluate the application of MCDM methods in LCM-DS. By using the Scopus and Web of Science databases as references, this study focuses on the identification of the following aspects related to the research in this field: distribution of scientific publications, most relevant sources, interaction dynamics among these sources, most prominent subjects in recent research (trend topics), and application of MCDM methods in LCM-DS. Regarding the latter, this study identified the Analytic Hierarchy Process (AHP) as the most used method in the LCM-DS since almost a quarter of the analyzed works applied it in the original, adapted, or hybrid (combined with other methods) format. Finally, our results show that MCDM methods are commonly applied to LCM-DS problems in all life cycle stages, mainly in development, utilization, and support. [ABSTRACT FROM AUTHOR]

Design for remanufacturing (DfRem) plays an important role and aims to reduce carbon emissions during the remanufacturing phase at the initial design stage. However, low-carbon requirements and customer demands are not considered integrally when generating schemes, which might to limit the potential to reduce carbon emissions. To address the problem, this paper proposes a DfRem scheme generation method that combines the Quality Function Deployment for Low-Carbon (QFDC) model with the FMAS (Functional-Motion-Action-Structure) model. Firstly, the demands are categorized into customer, remanufacturability and low-carbon demands, and the FAHP (Fuzzy Analytic Hierarchy Process) is used to evaluate the weight of demands. Secondly, the QFDC model is developed to convert demands to engineering characteristics, and to determine the design priorities. Thirdly, the FMAS model is established to map engineering characteristics into related structures, and a low-carbon and customer-satisfied DfRem scheme is generated. Finally, the efficacy of proposed method is demonstrated through a case study on the remanufacturing of a CNC milling machine, displaying its superiority in reducing carbon emissions while meeting customer demands. [ABSTRACT FROM AUTHOR]

In response to Japan's ambitious pursuit of carbon neutrality by 2050, this paper investigates the potential for tidal power generation in the Seto Inland Sea (SIS), Japan, utilising high-resolution ocean modelling and an analytic hierarchy process (AHP) combined with GIS-based spatial analysis. The analysis incorporates a 100 m resolution tidal current and water depth layers from the ocean model. The criteria used for evaluation were divided into main criteria, namely, proximity to existing infrastructure, wave height, and shipping density, and subcriteria, namely, distance from ports, power stations, highly populated areas, and coastlines. The identified optimal locations include the Naruto Strait, Akashi Strait, Matsushima Island, Hanaguri Strait, Funaori Strait, Taizaki Island, Kurushima Strait, Obatake Strait, and Tsuwaji Strait. With a focused analysis of the Obatake Strait in Yamaguchi Prefecture, analytical assessments of potential tidal power were conducted by considering two tidal turbines, Openhydro and Voith. The results indicate a power supply for approximately 100,000 households and a reduction of approximately 198,000 t-CO 2 per year in the most optimistic scenario. In a less optimistic scenario, with the installation of only 10% of the maximum capacity, a power supply for approximately 10,000 households and a reduction of approximately 19,800 t-CO 2 per year are observed. As Japan targets carbon neutrality by 2050, this research offers vital and practical insights for policymakers, energy planners, and environmentalists, identifying the Seto Inland Sea as a strategic area for tidal power development, aligning with Japan's commitment to a sustainable and resilient energy landscape. • High-resolution ocean model used with GIS for optimal site selection of tidal power • The Seto Inland Sea is vital for tidal power with optimal sites equals to 1.18 km2. • Tidal power quantification is based on the dominant tidal velocity • 10% of tidal power in Obatake Strait supplies 60% of Yanai City households • 10% of tidal power in Obatake Strait resulted in 19,800 t-CO 2 reduction per year [ABSTRACT FROM AUTHOR]

As blockchain technology merges with Mobile Edge Computing (MEC) and the Internet of Things (IoT), we encounter increasing challenges such as high energy consumption and latency due to the network's scale and complexity. Therefore, optimizing these communications and effectively managing computational task offloading is crucial, with data security being an essential concern. This paper studies these issues by examining networks that already operate within blockchain environments, where the complex process of transaction validations intensifies the demands on the system. We propose a new solution through the A3C-AHP offloading framework, which integrates the Asynchronous Advantage Actor-Critic (A3C) algorithm with the Analytic Hierarchy Process (AHP). This combination optimizes task offloading for multiple IoT users in MEC settings. The A3C algorithm improves decision-making by allowing agents to learn and adjust policies simultaneously, while AHP helps systematically evaluate and prioritize different network elements. Our framework adeptly manages the trade-offs between energy use, latency, and security when implemented in a blockchain context. Simulation results show that the A3C-AHP model notably enhances performance, cutting energy consumption by approximately 15.4 %, computational overhead by 49.5 %, latency by about 9.1 %, and operational costs by 8 % for networks with 100 users, highlighting its effectiveness and practical relevance. [ABSTRACT FROM AUTHOR]

A comprehensive understanding of the thermal runaway (TR) and combustion characteristics of lithium-ion batteries (LIBs) is vital for safety protection of LIBs. LIBs are often subjected to abuse through the coupling of various thermal trigger modes in large energy storage application scenarios. In this paper, we systematically investigated the TR and combustion characteristics of heating + overcharge and heating + short circuit at different temperatures and compared them with individual heating, overcharge, and short circuit. Additionally, we analyzed the TR and combustion hazards of different thermal triggering modes using Analytic Hierarchy Process (AHP). The results show that heating + overcharge has a shorter time of safety valve opening and TR , a lower thermal runaway temperature, a higher peak heat release rate (HRR), and is more hazardous than heating and overcharge. Compared with heating, heating + short circuit shortens safety valve opening time and increases peak HRR ; versus short circuit, heating + short circuit lowers TR temperature and TR time, enhances peak HRR , and causes a higher hazard. The AHP analysis indicates that the TR temperature and fire growth index are the most critical parameters and that heating + overcharge has the biggest TR and combustion hazards; besides, heating + short circuit exists higher TR risk and hazards than short circuit and greater combustion risks and hazards than heating. The research findings can provide valuable guidance for protecting and preventing energy storage LIBs TR. • Investigate the behavior of thermal runaway and combustion properties of LIBs with varying coupled trigger modes. • The external short circuit shortens the valve opening time and increases the peak heat release rate. • The greatest risk and hazard of thermal runaway and combustion occurs when heating and overcharging are combined. [ABSTRACT FROM AUTHOR]

Far-sea ship repair and maintenance capability evaluation is a typical complex system capability evaluation problem, and the corresponding evaluation indices include additional quantitative and qualitative indices. With the development of modern naval ships, higher requirements have been put forward for far-sea ship repair and maintenance. To accurately evaluate the capabilities of a naval ship's repair and maintenance system far at sea, a hybrid evaluation method based on binary semantic information and the evidential reasoning approach is proposed. First, we construct an evaluation indicator system to assess the capability of naval ship repair and maintenance systems. Second, based on binary semantic information and the analytic hierarchy process, a group expert weighting method is proposed to determine the weight distribution of the indicators. Finally, to address the multiattribute problem of the indicator system, a comprehensive evaluation method is proposed based on the evidential reasoning approach. The results of the calculation examples show that the proposed group expert weighting method and the hybrid evaluation method are feasible for capability evaluation of a naval ship's repair and maintenance system far at sea. By evaluating the calculation results, we can determine advantages and disadvantages in far-sea ship repair and maintenance, and through the sensitivity analysis of the evaluation indices, we can explore the contributions of different indices to the far-sea ship repair and maintenance capability, which can provide a theoretical reference for evaluating far-sea ship repair and maintenance. The results indicate that the method proposed in this paper can also be used as a general method in other similar studies. [ABSTRACT FROM AUTHOR]

The life cycle includes the "planning stage – construction stage – operation stage" of a project. For soft soil subgrade, life-cycle quality management refers to the construction stage and operation stage. The health of soft soil subgrade in the operation stage cannot be separated from the influence of other factors, such as maintenance technology, operation management and construction technology. Only relying on the monitoring data of the construction stage cannot satisfy the requirements of comprehensive evaluation of soft soil subgrade. Currently, there is no perfect information management system to store, process and analyse all the index data from construction stage to the operation stage. This paper puts forward indexes that are suitable for evaluating the health of soft soil subgrade. Among all these indexes, we selected 8 indexes to evaluate the construction stage subgrade health, and chose 13 indexes to evaluate the operation stage subgrade health. In this paper, the Analytic Hierarchy Process was employed to structure the judgment matrix of each level indexes and calculate the weight of each index. In this way, we established soft soil subgrade life-cycle health assessment system. We found that construction stage and operation stage contribution the weight of 30% and 70% to the health of expressways soft soil subgrade lifecycle. Respectively, for construction stage subgrade health, the greatest influence come from apparent indexes and weight reached 0.75. For operating stage subgrade health, the greatest influence come from internal indexes and weight reached 0.5813. The assessment system was used to evaluate and analyse the health condition of an expressway section with soft soil subgrade. It is found that slope problem is the main problem that affects the health of the soft soil subgrade in this section. Based on the situation, suggestions for improving the health of the subgrade and key points being noted in future operation are given. [ABSTRACT FROM AUTHOR]

• Identified 30 agro-ecosystem specific sustainability indicators. • Sustainability indicators help in mapping the climate resilience of agriculture. • We propose a framework, "Climate Risk Management Package for Agriculture (CRiMPA)", to aid in planning interventions. The impending threats of changing climate have been well documented across sectors. The climate risks are best addressed through increasing adaptive capacity and building resilience. Ever since the global call during the Rio Summit in 1992 for establishing sustainability indicators across sectors, there have been several studies across the world on developing indicators for sustainability, vulnerability and climate resilience. Agriculture, the most vulnerable system to changing climate, depends on the resilience of both social and ecological systems. This paper focuses on integrating the variability of climate into the agricultural sustainability measurement with a broad base of indicators and bringing in the localized factors for representing the agroecosystem specificities. The paper also aims at identifying indicators for measuring climate resilient agriculture in Indian sub-continent and developing a conceptual framework for profiling the spatial resilience across various agro-ecosystems for appropriate location-specific policy interventions. In the current study 1209 indicators used in various research studies were screened, grouped for similarity and purpose and classified based on the various dimensions viz., social, economic, ecological, etc. After a critical review based on their appropriateness as a measurable indicator, extent of overlap, relevance in Indian context and possible data availability, 41 indicators were shortlisted for validation through a comprehensive structured online survey among subject matter specialists (n = 225). The responses from the experts (n = 36) were analysed using weighted sum model (WSM) and analytic hierarchy process (AHP). The study identifies a list of 30 sustainability indicators for climate resilient agriculture in India, that are particularly suitable for different agro-ecosystems of the sub-continent. The authors advocate an action-oriented model called Climate Risk Management Package for Agriculture (CRiMPA) to aid in planning spatial/agro-ecosystem specific interventions, which in turn could strengthen the National Action Plan for Climate Change (NAPCC) of Government of India. [ABSTRACT FROM AUTHOR]

Since the use of LNG as an alternative fuel has drawn increasing attention from the marine industry, this paper aimed to evaluate three competitive LNG fuelled engine systems: ultra-steam turbine, four-stroke medium speed engine, and two-stroke low-speed engine systems. To achieve this goal, the paper developed an enhanced hybrid decision-making model which was applied to integrate the economic, environmental and technical performance of these systems. This model can be represented as a semi-quantitative multi-criteria decision making process in combination of several novel techniques, particularly 'life cycle cost assessment' for economic analysis, 'life cycle assessments' for environmental analysis, 'fuzzy order preference by similarity to ideal solution' for technical analysis and 'fuzzy analytic hierarchy process' for multi-criteria decision making. A case study with a 174 K LNG carrier has revealed that the two-stroke low-speed engine system is the most effective overall and suggested that this type of engine system will hold the lead over the other candidates in the large LNG carrier market. It has also demonstrated the effectiveness of the proposed model to improve the inherent subjectivity in existing qualitative multi-criteria decision-making processes by guiding the overall process in a more objective direction. Finally, this paper has revealed an underlying novelty of the proposed model to enhance the level of confidence level in the decision by expanding our short-term perspective to the holistic one. • The strengths and limits of three different marine LNG engine systems were investigated in various aspects. • The effectiveness of an enhanced hybrid MCDA model was demonstrated by evaluating an optimal marine LNG engine system. • It was ultimately suggested that the two-stroke engine systems would be the best option. • The impact of the proposed model is expected to extend to various studies related to proper decision-making. [ABSTRACT FROM AUTHOR]

The utilization of renewable energy sources has come into prominence especially over the last two decades. In the literature, various methods have been utilized for the evaluation of renewable energy sources. In particular, multi-attribute decision making (MADM) methods have been widely used throughout the renewable energy literature for several purposes such as evaluation of energy policies, selection of the most suitable renewable energy source for electricity generation, evaluation of renewable energy sources, identification of the optimal site for a renewable energy facility, and selection of the best one among energy alternatives. In the scope of this paper, the studies employing MADM methods in renewable energy applications have been taken into consideration. The main aim of the study is to determine the reasons and factors explaining why these methods have been employed. It can be concluded that Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), ELimination Et Choix Traduisant la REalité (ELECTRE) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) have come into the forefront as the most widely employed methods in the literature. However, there are a few studies employing outranking methods, ELECTRE and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) for the purpose of evaluating renewable energy investments/projects. Furthermore, in the literature, there are limited papers considering utilization of renewable energy sources such as geothermal, hydro, and waste. Finally, this study indicates that renewable energy exploitation is a quite suitable topic to use MADM methods. • Past studies are analyzed to identify trends and patterns in renewable energy use. • The very recent MADM studies on renewable energy have been summarized. • Graphical illustrations have been used to summarize the literature review results. • Comparative tabular literature reviews have been presented. • The most used MADM methods on renewable energy evaluation have been focused. [ABSTRACT FROM AUTHOR]

Fog computing uses fog nodes (FNs) near end devices to serve user applications in a highly virtualized environment. FNs are vulnerable to overloading because of the large number of user applications requesting service and their heterogeneous resource requirements. The proposed paper concentrates on maintaining FN in optimal working condition guaranteeing its operational efficiency and quality of service (QoS). This paper presents two methods for workload classification and overload prediction in FN, viz., a threshold-based technique adopting the criteria inferred from experimental results and a method based on Hidden Markov Model (HMM). The paper recommends virtual machine (VM) migration as a solution for avoiding the predicted overloading of FN through a hybrid multiple attribute decision making (MADM) method, for selecting the VM for migration, and an algorithm for finding the destination FN willing to host the migrating VM. Experimental results validate the proposed solution. [ABSTRACT FROM AUTHOR]

Abstract Exposure to an aggressive marine atmosphere can seriously harm reinforced concrete (RC) structures and affects a building's service life. In particular, buildings close to the sea are at high risk of suffering damage, mainly due to the effects of chloride. The scientific and technical communities are interested in studying new parameters related to building degradation, including "exposure to aggressive environments" in order to predict a building's service life and schedule maintenance and monitoring systems. This paper proposes a marine exposure index aimed at quantifying potential risks and damage to RC building structures. The definition of the index includes three synergistically related techniques: i) the Analytic Hierarchy Processes to analyze the complexity of the problem and the parameters involved in marine exposure; ii) a state-of-the-art technique to evaluate the degree of building degradation; iii) an optimization calibration procedure by setting a Mathematical Programming problem. The resulting index can be extensively and fruitfully applied by researchers and practitioners in order to assess the building's exposure to an aggressive marine atmosphere. Architects and engineers could apply the proposed index in any phase of the building process, from the project to the maintenance and management phases. The effectiveness of the proposal was tested in a survey of 1816 buildings on the Valencia coast (Spain). Graphical abstract Unlabelled Image Highlights • Marine atmosphere can seriously harm reinforced concrete structures. • This paper proposes a new marine exposure index. • The definition of the index includes three synergistically related techniques. • The index can be used to assess a building's exposure to a marine atmosphere. • The index has been calibrated by surveying close to two thousand buildings. [ABSTRACT FROM AUTHOR]

The process of selecting new uses for heritage buildings needs to consider a number of crucial criteria in order to determine and select the optimum option. The inappropriate selected use of a heritage building can lead to lose its value. This paper aims to introduce an appropriate evaluation tool to support the efficiency in selecting the optimum solution. The integrated multi criteria decision-making tools are used to support decision making in such cases (problems involving multiple criteria). Several MCDM tools have been developed for choosing the optimal probable options. Each tool has its own characteristics in finding the best alternatives. The Analytic Hierarchy Process, (AHP) that was developed by Professor Thomas Saaty in the late 1970s, was the most suitable tool for this study. The software selected and used in this work was Microsoft Excel. Aziza Fahmy Palace was selected as the case study in this paper. There are four suggested alternatives; which are: hotel, museum, office building and mixed uses. Using the application of AHP, the result showed that the best use is mixed uses with the highest value, which is 0.30 (30%), followed in sequential order by museum, office building and hotel. [ABSTRACT FROM AUTHOR]

Highlights • MCDM has been useful to overcome the choice problem in mining and mineral processing. • AHP has been the most used MCDM technique in this area of research. • A large proportion of the published papers make use of hybrid methods. • This is the first review on the use of MCDM for the choice problem in this area. Abstract Despite the fact that the potential of multi-criteria decision making (MCDM) to overcome a variety of problems in mining and mineral processing has been widely recognised, no literature review in these fields has been conducted. This manuscript addresses this issue by providing a comprehensive overview of the applications and trends of MCDM methods for the choice problem (i.e., determining the best option from a set) in mining and mineral processing. 90 articles published between 1999 and 2017 were selected following a searching methodology and eligibility criteria detailed in this manuscript. In addition, for the purpose of the survey, different types of selection problems were identified. The results show that there are two phases of growth in the application of MCDM techniques to the choice problem in mining and mineral processing. The first phase, from 1999 to 2007, shows a very low number of publications with only a moderate increase by the end, whereas the second phase, from 2007 to 2017, shows a significant growth in the number of published articles. The review also shows that the most addressed problem has been the selection of mining methods, while the Analytical Hierarchy Process (AHP) has been the most used MCDM method. The rise in the application of hybrid MCDM methods is also discussed. This review paper provides insight into the current state of applications of MCDM in mining and mineral processing and discusses pathways for future research directions in the development of MCDM methods that would benefit these fields. [ABSTRACT FROM AUTHOR]

Abstract Optimization allocation of agricultural water and land is a very complex system involves multiple objectives. Moreover, weights of each objective were signed by subjective judgement of decision makers is unreasonable. Furthermore, uncertainties are inevitable in the optimization allocation of irrigation water and land. In order to solve the above problems, this paper developed an improved multi-objective stochastic fuzzy programming method. The developed model was then applied to a case study in Wuwei City, Gansu Province, China. Maximum net benefit, maximum agricultural water productivity, and minimum irrigation area were regarded as planning objectives. A series of optimal irrigation and planting structure schemes were obtained under multiple uncertainties. From the results, water resources shortage in Wuwei city is very severely and it could not satisfy Wuwei's water demand even if the risk probability P i reaches 0.25. Moreover, water and irrigation area would vary in different crops. Such changes would mainly take place in potato, vegetable and cucurbit, which have the same characteristics with higher yield, lower cost or lower irrigation quota than other crops. Furthermore, the decision makers could make reasonable decisions on the optimal use of irrigation water and land resources under multiple objective and uncertainties based on the obtained results. Highlights • This paper developed an improved multi-objective stochastic fuzzy programming method. • It simultaneously optimizes irrigation water amount and irrigation areas. • AHP method was introduced to assign weight of each objective. • Optimal irrigation schemes were obtained under multiple uncertainties. • It could be helpful to make decision under multiple uncertainty and multiple objectives. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a hybrid subjective and objective evaluation method of the equipment for first-class distribution network. Firstly, it analysis the difficulties of the equipment selection in the current first-class distribution network. Secondly, it deeply analysis the influencing factors of equipment selection in the first-class distribution network. The comprehensive evaluation indices system of first-class power distribution network equipment is constructed from five aspects including economy, performance, intelligence, coordination, and standardization of equipment, in order to the features of the equipment for power distribution network, such as diversity of equipment functions, diverse evaluation indicators, various types, and varied access methods. The subjective weighted methods are highly subjective and difficult to fully express the effectiveness of weights for evaluating indicators. The objective weighted methods are easy to lose key information due to limited sample of measurement data. A hybrid subjective and objective weighting method is proposed to combined with principal component analysis and analytic hierarchy process, and the relative entropy principle is used to weight distribution of subjective and objective evaluation results. Finally, the feasibility of the proposed method is verified through the first-class distribution network equipment in a province in southern China. This paper provides reference for comprehensive evaluation of first-class distribution network equipment. [ABSTRACT FROM AUTHOR]

Abstract The work presented in this paper proposes an efficient routing protocol named AHP-based Multimetric Geographical Routing Protocol (AMGRP) as it adopts an Analytical Hierarchical Process (AHP) while considering multiple routing criteria such as mobility metric, link lifetime, node density and node status which have been accepted as crucial factors for better performance of a protocol. The protocol implements the computed single-weighing function to identify a next hop node within a defined range which can ensure an enhanced forwarding process. The simulation results in the paper have proved that the designed protocol performs better when compared with GPSR and SLD-GEDIR protocols in an obstacle modelled urban vehicular environment. [ABSTRACT FROM AUTHOR]

With the development of smart grid technology in China, the study of low frequency oscillation early warning has become an important element of power system stability research. Aiming at the problems of single warning indicator with poor accuracy and lack of online warning system in the early warning strategy of low frequency oscillation in power system, a comprehensive low frequency oscillation early warning algorithm based on the evaluation method of kernel matrix hierarchical analysis of fuzzy comprehensive is proposed. Firstly, this method screens out the original data collected by Phasor Measurement Unit (PMU), and extracts the key data volume to form multiple early warning indicators, and generates the trapezoidal fuzzy number judgment matrix. Secondly, by calculating the kernel matrix and consistency test, it is determined whether or not the generated fuzzy matrix is reasonable and calculate the relative weights of the evaluation indicators. The affiliation function is constructed for each early warning indicator. A comprehensive indicator is calculated for multiple indicators, and the reasons of low frequency oscillation in power system are classified by the Random Forest (RF) algorithm. Then, the low-frequency oscillation system is constructed, and the algorithm convergence is proved by the Lyapunov indirect method. The algorithm can automatically determine whether low frequency oscillation occurs or not and classify different types of low frequency oscillations online. Finally, the correctness and validity of this paper's method is verified by a New England 10-machine 39-node system. Compared with the traditional Analytic Hierarchy Process (AHP) method, the proposed method in this paper greatly improves the accuracy of early warning and meets the need of online warning. [ABSTRACT FROM AUTHOR]

Due to more and more awareness of environmental conservancy and sustainable development, automated container terminals (ACTs) have gained increasing attention and become popular worldwide. However, there is a crucial challenge in implementing ACTs, i.e., how to develop terminal layout planning (including terminal layout and facility selection) to realize performance goals. Focusing on this challenge, the aim of this paper is to resolve how to appropriately select terminal layout and facilities in ACTs with respect to various performance criteria. Several research limitations can be gathered from the existing literature: (i) Most of the existing works mainly develop optimization technologies to tackle layout optimization and facility comparison issues within a few types of terminal layout and facilities, yet few researchers have proposed evaluation methods for making selection decisions on terminal planning. (ii) Only a few types of criteria are considered, and requirements and preferences of different participants are ignored, not to say realizing an optimal compromise by employing comprehensive criteria weights in evaluation processes. (iii) New technological improvement in ACTs has not received much attention, and there still lacks a method to precisely quantify the concerned criteria. Accordingly, this paper introduces a criteria system comprising economic, environment, social, resource and performance groups and develops an agent-based simulation method considering different terminal layout and facilities to determine criteria values. A multi-criteria decision making (MCDM) framework is proposed for making the most reasonable and appropriate selection decisions, which employs a variation coefficient weighted method to calculate comprehensive criteria weights, which integrate subjective and objective weights obtained from AHP (analytic hierarchy process) method and entropy weight method. To overcome rank reversal problems in the TOPSIS (technique for order preference by similarity to an ideal solution) method, a new improved rank reversal robust TOPSIS method, called NR-TOPSIS, is utilized to rank and select alternatives, which is ranking stable in the experiments performed. An illustrative application on a container terminal in China demonstrates the effectiveness of the proposed MCDM method and sensitivity and comparative analysis verifies the robustness and stability of the method. [ABSTRACT FROM AUTHOR]

Harmonic distortion levels in current power systems have increased due to technical advancements in industrial and renewable energy applications. So far, passive power filters have been widely employed to minimize harmonics and lessen their adverse effects. In this regard, this paper presents a novel bi-level design of damped double-tuned passive filters operating in a non-sinusoidal power system with nonlinearities at both the source and the load. A modern metaheuristic optimization technique known as wild horse optimization is applied to acquire the parameters of the used filters. Several objective functions, such as voltage total harmonic distortion, current total demand distortion, active power losses, and resonance-based metric minimization, were researched to improve the analyzed system's overall power quality performance. The mathematical derivations of the filter design expressions are given in detail. In the literature, there are several schemes for damped double-tuned filters. This paper investigates and analyses four schemes of this filter. The results are compared to those obtained from other metaheuristic optimization algorithms to ensure that the proposed algorithm produces the most effective outcomes. Statistical analysis is performed using many criteria to ensure the superiority of the proposed algorithm. Furthermore, depending on several assessment criteria, the analytical hierarchy process is employed to find the most effective candidate scheme. One of the schemes tested (scheme B) outperformed the others. [ABSTRACT FROM AUTHOR]