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Failure modes and effects analysis (FMEA) is a systematic approach that focuses on evaluating critical disturbances in a system. However, traditional FMEA has its own drawbacks, such as invalid computations and ambiguous priority definitions, which lead to many constraints in the application of complex production processes, especially in job shops with various resources. Therefore, this paper proposes an analytic disturbance prediction method for job shop with multiple resources and multiple evaluation indexes, which combines the vector computing techniques, FMEA, and fuzzy analytic hierarchy process (FAHP). In contrast to other work, this paper focuses on the establishment of FMEA mathematical model to improve the readability of multi-resource disturbance risk results. To this end, the projection of the disturbance vector is visualized to reduce repeated calculation results, triangles and trapezoids are used as membership functions to improve the accuracy of weight, and the differentiation index is used to reduce the ambiguity of priorities. The proposed method can effectively discover the critical disturbances and enable managers to undertake more assertive decisions.

Spring Outing Painting of Madam Guo is one of the representative works of Zhang Xuan, a famous Chinese court painter of the Tang dynasty (618–907), who was the “leader” of the trend of figure painting in the Tang dynasty and had a great influence on later figure painting. The costumes of the characters in the paintings not only show the artistic aesthetics of the prosperous Tang dynasty, but also reflect the rich cultural connotation. At present, the research on this painting is mainly about character discrimination and painting appreciation. There are few studies involving the costumes in this painting. With the rapid development of digital clothing technology, it provides a new way and path for the restoration of ancient costumes. Based on the costume archaeology of Spring Outing Painting of Madam Guo, this paper uses 3D virtual simulation and reverse engineering technology to restore the costume style of the characters in the picture, realize the digital restoration and protection of the style drawing, paper pattern, and 3D simulation drawing of the characters’ costumes in the picture. Finally, we introduce the fuzzy analytic hierarchy process (FAHP) to comprehensively evaluate the costume restoration effect. Our proposed method solves the problem of the constraints of time and space on the presentation of ancient traditional costumes, promotes the excellent historical culture of China, and provides a certain reference for the modern redesign of ancient costumes.

In this paper, the application of hexagonal fuzzy multiple-criteria decision-making (MCDM) methodology for the site selection of electric vehicle charging stations is considered. In this regard, four factors and thirteen sub-factors have been taken into consideration for E-vehicle charging site selection. In this research, the geographic information system (GIS) has been incorporated with MCDM techniques. The fuzzy analytic hierarchy process (FAHP) is used to obtain a fuzzy weight of factors and sub-factors. MCDM tools fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) and fuzzy complex proportional assessment (FCOPRAS) have been used to rank the selected sites. A centroid-based method for defuzzification and distance measure between two hexagonal fuzzy numbers (HFN) has been developed for this paper. A practical example in Howrah, India, is considered to show the applicability and usefulness of the model. The results depict the suitability of the proposed research. Comparative and sensitivity analyses have been demonstrated to check the reliability, robustness and effectiveness of the proposed method.

This paper addresses the problem of evaluating vehicle failure modes efficiently during the driving process. Generally, the most critical factors for preventing risk in potential failure modes are identified by the experience of experts through the widely used failure mode and effect analysis (FMEA). However, it has previously been difficult to evaluate the vehicle failure mode with crisp values. In this paper, we propose a novel hybrid scheme based on a cost-based FMEA, fuzzy analytic hierarchy process (FAHP), and extended fuzzy multi-objective optimization by ratio analysis plus full multiplicative form (EFMULTIMOORA) to evaluate vehicle failure modes efficiently. Specifically, vehicle failure modes are first screened out by cost-based FMEA according to maintenance information, and then the weights of the three criteria of maintenance time (T), maintenance cost (C), and maintenance benefit (B) are calculated using FAHP and the rankings of failure modes are determined by EFMULTIMOORA. Different from existing schemes, the EFMULTIMOORA in our proposed hybrid scheme calculates the ranking of vehicle failure modes based on three new risk factors (T, C, and B) through fuzzy linguistic terms for order preference. Furthermore, the applicability of the proposed hybrid scheme is presented by conducting a case study involving vehicle failure modes of one common vehicle type (Hyundai), and a sensitivity analysis and comparisons are conducted to validate the effectiveness of the obtained results. In summary, our numerical analyses indicate that the proposed method can effectively help enterprises and researchers in the risk evaluation and the identification of critical vehicle failure modes.

Technology advancement in power–electronic interfaces and their evolution open an opportunity to end-users to benefit from their newfound capability. For the end-users, power–electronic interfaces can act as Distributed Energy Resources (DERs) for reactive power injection and absorption. If these power–electronic interface capabilities can be properly integrated into traditional utility system operations, they can be used as beneficial tools for distribution management and voltage profile enhancement. Considering the present distribution system, it is not possible to communicate to all DERs. In this paper, we considered two proposed residential-control and droop-control methods. The multi-criteria decision-making technique (MCDM), along with fuzzy theory, was used to prioritize candidate buses for their participation in the Volt-VAR program. In this paper, the contribution of active DERs in reactive power compensation was evaluated.

The present paper emphasizes on the development of a hierarchical model using Fuzzy Multiple Attribute Decision Making (FMADM) method for the selection of E-learning websites. The working of the model developed in this research mainly consists of three steps: (i) Summarization and identification of selection indexes, (ii) Selection indexes weights calculations using Fuzzy Analytical Hierarchy Process (FAHP) and (iii) Ranking of alternatives by implementing three MADM analytical methods as Complex Proportional Assessment (COPRAS), Visekriterijumsko Kompromisno Rangiranje (VIKOR) and Weighted Distance Based Approximation (WDBA). In order to demonstrate the applicability and utility of the proposed methods, an empirical example related to the selection of E-learning websites that are widely used to learn the ‘C’ Programming Language for the software development is carried out. In addition, the results of these three methods are also compared to analyze the critical aspects of the selection indexes. It strongly shows that the developed FMADM model of this paper could be an efficient and effective assessment tool.

People use mHealth applications to help manage and keep track of their health conditions more effectively. With the increase of mHealth applications, it has become more difficult to choose the best applications that are user-friendly and provide user satisfaction. The best techniques for any decision-making challenge are multi-criteria decision-making (MCDM) methodologies. However, traditional MCDM methods cannot provide accurate results in complex situations. Currently, researchers are focusing on the use of hybrid MCDM methods to provide accurate decisions for complex problems. Thus, the authors in this paper proposed two hybrid MCDM methods, CODAS-FAHP and MOORA-FAHP, to assess the usability of the five most familiar mHealth applications that focus on type 2 diabetes mellitus (T2DM), based on ten criteria. The fuzzy Analytic Hierarchy Process (FAHP) is applied for efficient weight estimation by removing the vagueness and ambiguity of expert judgment. The CODAS and MOORA MCDM methods are used to rank the mHealth applications, depending on the usability parameter, and to select the best application. The resulting analysis shows that the ranking from both hybrid models is sufficiently consistent. To assess the proposed framework’s stability and validity, a sensitivity analysis was performed. It showed that the result is consistent with the proposed hybrid model.

Performance evaluation of any financial institution is extremely important to look after the health and prospect of the institution. In many research of performance evaluation analysis of banks, several ratio parameters are used mostly in statistical analysis. Designing effective and comprehensive model for evaluation process of financial matters in banking sector is complex due to multiple criteria and parameters, mostly uncertain in nature. This paper presents a comprehensive process considering several financial criteria of several alternatives on the basis of several expert’s (decision maker’s) opinion and subjective judgment. Intensity of importance is represented in fuzzy scale. We used fuzzy AHP-preference programming (FPP) to obtain priority weights associated with each criteria and compromise ranking method (VIKOR) considering Market Capital, Net Sales, Net Profit, Total Assets, and Other Income in ranking alternatives. A case study involving ten active Indian Public Sector Unit (PSU) banking industries is undertaken to illustrative the feasibility of the suggested approach. A sensitivity analysis is also carried out for checking the method reliability.

Due to the increased spread of invasive animals and plants in the territory of Latvia, the necessity of ecological risk assessment related to such kind of spread has grown lately. In cases with sufficient statistical data, the risk assessment may be successfully performed on the basis of statistical methods. The amount of statistical data in the context of spread of invasive animals and plants is pretty poor; therefore, the only method of ecological risk assessment remains subjective judgements of experts. The present paper proposes using a programming tool for ecological risk analysis elaborated by the authors. With the help of this programming tool the method of Fuzzy Analytical Hierarchical Process is implemented. The elements of the pair- wise comparison matrix are allowed to be expressed by triangular and trapezoidal fuzzy sets. The presented tool makes it possible to design the fuzzy pair-wise comparison matrix and process the results in a user-friendly way.

The COVID-19 pandemic has boosted the growth of the online food delivery (OFD) market in every corner of the world. In Vietnam, the food delivery service is rising rapidly and opening a large gateway of opportunities for numerous OFD platforms, also making it a competing business market in this country. Thus, to keep up with the ever-changing market dynamics, there are numerous measures and dimensions for the OFD entrepreneurs to take into consideration towards sustainable development. This paper’s objective is to evaluate major OFD companies in Vietnam based on a comprehensive set of criteria, which are social and environmental criteria (healthy and safety, information security, and environmental impact), economic criteria (delivery cost, operational capability, and risk management), service quality (order fulfillment, delivery speed, convenience of payment, online/offline service level, and customer feedback), and technology (web design, real-time tracking systems, and marketing techniques). To achieve this objective, this work proposes a multi-criteria decision-making (MCDM)-based framework combining the fuzzy analytic hierarchy process (FAHP) and the weighted aggregated sum product assessment (WASPAS). The FAHP is used to generate criteria weights in which fuzzy set theory is applied to translate the linguistic evaluation statements of experts. Then, WASPAS is used to rank the OFD companies against the selected criteria. The evaluation criteria that have obtained maximum weight priority in the FAHP analysis are “convenience of payment”, “delivery speed”, “online service level”, “order fulfillment”, and “delivery cost”. From the final ranking of WASPAS, Foody is today the best performing OFD player in Vietnam regarding the selected criteria, followed by GrabFood and Now. The proposed methodology can be an accurate and robust evaluation model for the industry, while the managerial implications of this study provide significant materials for decision-makers in the OFD market in improving their businesses towards sustainable development.

In recent years, much more emphasis than before has been placed on fire safety regulations by the local and central authorities of China, which makes fire risk assessments more important. In this paper we propose a new fire risk assessment approach for large-scale commercial and high-rise buildings that aims to evaluate the performances of their fire safety systems, this should improve the fire risk management and public safety in those buildings. According to the features of large-scale commercial and high-rise buildings, a fire-risk indexing system was built, and based on it we established a scientific fire risk evaluation system. To this end, the fuzzy analytic hierarchy process (FAHP) was used to assign a reasonable weight to each fire risk factor in the evaluation system. In addition, we revised the original scores by analyzing the coupling relationships among the fire risk factors. To validate our system, we selected 11 buildings in Shandong province and collected their fire safety data. Then, we calculated the final scores for the fire safety management of those buildings, and the results show that: (1) our fire risk evaluation system can assign reasonable weights, (2) the proposed evaluation system is comprehensive and has strong interpretability, since it exploits the coupling relationships among the risk factors. The novelty of the proposed approach lies in that it integrates opinions from multiple experts and utilizes coupling relationships among the factors. Further, the feedback from the approach can find not only the weaknesses in fire risk management, but also the potential causes of fires. As a result, the feedback from our assessment can assist the safety chiefs and inspectors with improving fire risk management.

The aim of the paper is to determine the risk level of a contract extension with the existing policyholders, which is further propagated to the business effectiveness and long-term sustainability of the company. The uncertainties in the relative importance of risk factors, their values, and risk levels are described by the linguistic forms, which are modeled by using the fuzzy sets theory. The evaluations of the relative importance of risk factors are stated as a fuzzy group decision-making problem. The weights of risk factors are obtained by using a fuzzy analytic hierarchy process. The determination of production rules for the assessment of the risk level is based on fuzzy IF-THAN rules. The verification of the model is performed by using real-life data originating from the insurance company which operates in the Republic of Serbia.

Nowadays, the supply chain has become a buzzword in the business field. The only supply chain can help to lead a business in an organized way. However, in a supermarket, the supply chain is very important, but they need to ensure better communication with the supplier, customer, and internal management too. Each factor of the supply chain has a good effect on itself. The purpose of this research is to explore the important supermarket supply chain factors found in the literature and from supply chain experts and to develop a framework which can help to arrange the criteria in a sequence from most important to the worst by considering each sector of the supply chain. This paper has studied one of the supermarkets in Bangladesh, namely Save ‘n’ Safe. Authors have taken FAHP, one of the tools of MCDM, to figure it out the most effective factors. The result reveals that managing inventory, internal information sharing, and accurate demand forecasting are the most affected factors for the Save ‘n’ Safe (a supermarket). Finally, some recommendations have been given to improve the existing situation. This study can be used not only in the other supermarkets but also any other retail or grocery shops.

The rapid popularization of multimode terminals that simultaneously run multiple services (such as browsing web pages during a video session) has brought a decent amount of attention to the network selection problem of multimode terminals. However, most network selection algorithms proposed for vertical handoff are only suitable for terminals running a single service. This paper proposes a network selection algorithm for multiservice multimode terminals in heterogeneous wireless networks. The algorithm considers user preferences, network attributes, and service characteristics. Entropy and fuzzy analytic hierarchy process (FAHP) are used to calculate the objective weights of the network attributes and the weights determined by the service characteristics, respectively. The comprehensive weights of network attributes are obtained by combining the user preferences and service priority. At the same time, different utility functions are used to calculate the utility values of the network attributes for multiservice. Finally, the simple additive weighting (SAW) method is used to synthesize the utility values and the comprehensives weights, while the most appropriate network is selected by a technique for order preference by similarity to an ideal solution (TOPSIS) and a threshold. The simulation results show that the proposed algorithm can accurately select the most appropriate network by considering different factors. Compared to the existing two MMT network selection algorithms, it can reduce the number of vertical handovers and obtain better user experience while satisfying user's preferences and service's requirements, thus solving the multiservice multimode terminals network selection problem.

Today's software complexity makes developing defect-free software almost impossible. Consequently, developing classifiers to classify software modules into defective and non-defective before software releases have attracted great interest in academia and software industry alike. Although many classifiers have been proposed, no one has been proven superior over others. The major reason is that while a research shows that classifier A is better than classifier B, we can find other research that shows the opposite. These conflicts are usually triggered when researchers report results using their preferable performance evaluation measures such as, recall and precision. Although this approach is valid, it does not examine all possible facets of classifiers performance characteristics. Thus, the performance evaluation might improve or deteriorate if researchers choose other performance measures. As a result, software developers usually struggle to select the most suitable classifier to use in their projects. The goal of this paper is to apply the fuzzy analytical hierarchy process (FAHP) as a popular multicriteria decision-making technique to reliably evaluate classifiers' performance. This evaluation framework incorporates a wider spectrum of performance measures to evaluate classifiers performance rather than relying on selected preferable measures. The results show that this approach will increase software developers' confidence in research outcomes and help them in avoiding false conclusions and infer reasonable boundaries for them. We exploited 22 popular performance measures and 11 software defect classifiers. The analysis was carried out using KNIME data mining platform and 12 software defect data sets provided by the NASA metrics data program (MDP) repository.

Choosing a supplier is a complex decision-making process that can reduce the total cost of production inputs and increase profits without increasing the price or sacrificing product quality. However, supplier selection processes usually involve multiple quantitative and qualitative criteria which increase the complexity of the problem and may decrease the accuracy and effectiveness of the process. Such complex decision-making problems can be supported by using multicriteria decision-making (MCDM) models. While there have been multiple MCDM models to support supplier selection processes in different industries and sectors, only a few are developed to support the supplier selection processes in the garment industry, especially under uncertain decision-making environment. This paper presents an integrated mathematical model under a fuzzy environment and applies it to the supplier selection process in the garment industry. In this research, the authors utilize the Buckley extension based fuzzy Analytical Hierarchical Process (FAHP) method in combination with linear normalization based fuzzy Grey Relational Analysis (F-GRA) method to develop a MCDM approach to the supplier selection process under a fuzzy environment. As a result, supplier 08 (SA08) is the optimal supplier. The contribution of this work is to propose an MCDM model for ranking potential suppliers in the garment industry under a fuzzy environment. The proposed approach can also be applied to support complex decision-making processes under a fuzzy environment in different industries.

In order to make the urban green electricity power a scientific, systematic and intuitive evaluation system, this paper briefly introduces the content and significance of green electricity, the research background, guidance significance and considerations of Strategic Environmental Assessment (SEA), the content and relationship between related factors of DPSIR framework model, the construction and correction of fuzzy complementary matrix and fuzzy consistent matrix. This paper applies the DPSIR framework model of Strategic Environmental Assessment to the evaluation of urban green electricity power. Based on applying fuzzy analytic hierarchy process (FAHP) method to determine the weight of each factor, this paper first establishes a more comprehensive and operational indicators evaluation system of urban green electricity power.

High competition between universities has been increasing over the years, and stimulates higher education institutions to attain higher positions in the ranking list. Ranking is an important performance indicator of university status evaluation, and therefore plays an essential role in students’ university selection. The ranking of universities has been carried out using different techniques. Main goal of decision processes in real-life problems is to deal with the symmetry or asymmetry of different types of information. We consider that multi-criteria decision making (MCDM) is well applicable to symmetric information modelling. Analytic hierarchy process (AHP) is a well-known technique of MCDM discipline, and is based on pairwise comparisons of criteria/alternatives for alternatives’ evaluation. Unfortunately, the classical AHP method is unable to deal with imprecise, vague, and subjective information used for the decision making process in complex problems. So, introducing a more advanced tool for decision making under such circumstances is inevitable. In this paper, fuzzy analytic hierarchy process (FAHP) is applied for the comparison and ranking of performances of five UK universities, according to four criteria. The criteria used for the evaluation of universities’ performances are teaching, research, citations, and international outlook. It is proven that applying FAHP approach makes the system consistent, and by the calculation of coefficient of variation for all alternatives, it becomes possible to rank them in prioritized order.

In recent years, the market of textile and garment materials has been volatile, and the ongoing US-China trade war is creating good opportunities for other markets such as Vietnam, Bangladesh and Mexico to continue to expand their market share in the United States. Vietnam is expected to have great advantages thanks to cheap labor cost and strong production capacity. Raw material supplier selection in a volatile competitive environment is crucial for a company to succeed, and supplier selection is a complicate process in which decision-makers must consider multiple quantitative and qualitative features, along with their symmetrical impact, in order to achieve an optimal result. The purpose of selecting the right supplier is to improve competitiveness and product quality, while satisfying customer demand at a minimum production cost. The aim of this paper is to propose a multicriteria decision making model (MCDM) for garment and textile supplier selection. In the first stage, all criteria affecting this process are defined by using the supply chain operations reference model (SCOR) and experts’ opinion. Incorporating hybrid fuzzy set theory into the analytical network process (ANP) model is the most effective tool for addressing complex problems of decision-making, which has a connection with various qualitative criteria; thus, the Fuzzy Analytical Hierarchy Process (FAHP) was applied for determining the weight of all potential suppliers, and the preference ranking organization method for enrichment of evaluations (PROMETHEE II) was used for ranking the supplier. The results of this research will assist researchers and decision makers in identifying, adapting and applying appropriate methods to identify the optimal material suppliers in the textile and garment industry. This research can also be used to support supplier selection decisions in other industries.

The reliability of the measurement system, accuracy, and precision are significant criteria at any measurement procedure. Strain gage sensors are one of the tools to measure the strain of structures in engineering applications. Different controllable and extraneous parameters will change the accuracy and precision of the strain gauges. As a result, it is valuable to investigate the most significant parameters and the percentage of their contributions affecting the strain measurement. This paper presents the multi-objective optimization in strain gauge measurements to determine the Reliability and Noise indices. The best set of parameters with a high-reliability index (which means low noise index) for strain measurement based on two significant objectives of accuracy and precision are evaluated. The significant parameters, their optimal levels and percentage of contributions are identified according to the Taguchi and Fuzzy Analytic Hierarchy Process (FAHP) with Technique for the Order Performance by its Similarity to the Ideal Solution (TOPSIS) methods. To obtain this evaluation, three levels (L1, L2, and L3) of temperature (P1), the length of wires (P2), and the point of applied force (P3) are considered. This configuration leads to L9 orthogonal array of Taguchi approach based on the number of parameters and their levels. The triangular membership function for the weightiness of accuracy and precision is used via AHP. By using the Taguchi method, the optimum set of parameters are identified as P1 at L1, P2 at L2, and P3 at L3 to have a higher reliability index compared to trial 8. By applying the optimum design of experiment, it is found that the reliability index is 95%. The results also show that the highest reliability index is related to trial 8 with 87.65% reliability. Finally, the combination of FAHP and TOPSIS with Taguchi method for multi-objective optimization is introduced and proposed as a practical and useful model to determine the best set of parameters with the highest reliability index in strain measurement. Refereed/Peer-reviewed

Evaluation and supplier selection is one of the important issues in the field of military supply chain management. The actions of a military organization to evaluate and select efficient suppliers play an important role in creating a competitive advantage and improving the organization's performance. This is more complicated when there are different goods to buy, as well as restrictions such as the demand for each product, the supplier's ability to deliver the goods, delivery time, product quality, and price. In this paper, the fuzzy analytic hierarchy process (FAHP) method and a choice mathematical model with genetic algorithm (GA) solving approach are used to solve the supplier selection and supply problem. This method solves the problem in three steps. In the first step, using the FAHP, the relative weights of each criterion are calculated for each commodity. In the second step, the score of each company is calculated for each criterion and for each commodity. Outputs from the first and second steps are used as inputs in the allocation model to determine the suppliers and the amounts that each should provide. In order to implement the proposed model, this method has been implemented on Haft Tir Industry of Isfahan and numerical results have been investigated to select the best supplier from 3 companies to purchase 3 products and have 4 criteria. The results showed that using the combined method of GA and the FAHP can solve the problem of mixed linear programming of supplier selection.

Cloud manufacturing (CMfg) is an innovative manufacturing paradigm in which geographically distributed various manufacturing resources are encapsulated into manufacturing services (MSs), and also these MSs can provide users with various services. Users can find and choose qualified MSs to form cliques to help them complete their manufacturing tasks via Internet. Trust makes cooperative endeavors happen. Hence, it is an important problem to evaluate the trustworthiness of MSs in CMfg. In this paper, we present a comprehensive assessment approach to evaluate the trustworthiness of a MS in CMfg. The approach evaluates a MS from both objective and subjective perspectives, named as credit assessment and reliability assessment, respectively. Multinomial logistic regression analysis is presented to assess the credit of a MS, while fuzzy analytic hierarchy process is used to assess its reliability. Finally, a case study is presented and the results show the comprehensive assessment approach is efficacious at the trustworthiness evaluation of a MS.

In Vietnam, as more and more organizations are moving toward globalization, green supplier selection (GSS) has emerged as a strategic approach in supply chain management that requires supplier practices in lessening the environmental risks to society. Based on both conventional and environmental criteria, this paper aims to evaluate a set of suppliers by establishing a multi-criteria decision-making (MCDM)-based framework using an integrated fuzzy analytical hierarchy process (FAHP) with the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. Initially, five GSS criteria of the environmental aspect (wastewater treatment, solid waste generation, energy consumption, air pollution, corporate social responsibility) and conventional criteria (quality, cost, delivery, and technology) are identified from the literature and consulting field experts to employ the MCDM approach. The trustworthiness of the proposed integrated framework is presented by discussing a case study in the coffee bean supply chain in Vietnam. The FAHP is used to generate criteria weights in which fuzzy set theory is applied to translate the linguistic evaluation statements of experts, and VIKOR is used to rank the alternatives against the selected criteria. From FAHP findings, the most important criteria are quantity discount, solid waste generation, order fulfillment rate, logistics cost, and purchasing cost. A consistency test is performed to ensure the uniformity of the expert’s input. The best suppliers are determined through the final ranking of the VIKOR model for the case study. The work presented provides insight to decision-makers of supplier selection that helps determine significant GSS criteria and aids in the minimization of environmental risks to society arising from the supply chain on corporate sustainability standards.

This paper presents a new approach for design concept selection by using an integrated Fuzzy Analytical Hierarchy Process (FAHP) and an Interval-valued intuitionistic fuzzy modified TOP-SIS (IVIF-modified TOPSIS) model. The integrated model which uses the improved score func-tion and a weighted normalized Euclidean distance method for the calculation of the separation measures of alternatives from the positive and negative intuitionistic ideal solutions provides a new approach for the computation of intuitionistic fuzzy ideal solutions. The results of the two approaches are integrated using a reflection defuzzification integration formula. To ensure the feasibility and the rationality of the integrated model, the method is successfully applied for evaluating and selecting some design related problems including a real-life case study for the selection of the best concept design for a new printed-circuit-board (PCB) and for a hypothetical example. The model which provides a novel alternative, has been compared with similar com-putational methods in the literature.

Due to rising concerns for environmental sustainability, the Indian electronic industry faces immense pressure to incorporate effective sustainable practices into the supply chain (SC) planning. Consequently, manufacturing enterprises (ME) are exploring the option of re-examining their SC strategies and taking a formalized approach towards a sustainable partnership with logistics providers. To begin with, it is imperative to associate with sustainable forward and reverse logistics providers to manage effectively the upward and downstream flows simultaneously. In this context, this paper proposes an integrated SC network for the evaluation and selection of forward distribution partners (FDP) and third party reverse logistic providers (3PRLP) from a sustainable perspective of an Indian electronic ME. The sustainable evaluation of the logistic partners is performed using fuzzy analytic hierarchy process and the technique for order performance by similarity to ideal solution. The integrated logistics network is modeled as a bi-objective mixed-integer programming problem with the objective of maximizing the profit of the manufacturer and maximizing the sustainable score of the selected forward and reverse logistics providers. The novelty of the study is its ranking of the FDPs and 3PRLPs on the economic, environmental, and social dimensions of sustainability and the simultaneous integration of logistics outsourcing decisions for the forward and reverse flow of products. Goal programming approach is utilized to capture the trade-off between the conflicting objectives and to attain a satisfying solution to the bi-objective problem. The results indicate that integrating the strategic decisions of selection of logistics partners with the operational flow planning decisions can immensely improve the sustainable performance value of the SC network and secure reasonable profits. The managerial implications drawn from the result analysis provide a sustainable framework to the ME for enhancing its corporate image.

The urban mobility system is an important factor in social development and must, therefore, be tackled in a way that enables balanced, sustainable development. The purpose of the present work was to introduce a new holistic approach to urban mobility system (UMS) planning, which involves a strategic decision-making process with a broad involvement of various stakeholders. For this purpose, an innovative model was created by synthesizing the focus group (FG) method with the nominal group technique (NGT), SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis, and the fuzzy analytical hierarchical process (FAHP) method. The fuzzy approach was chosen for its ability to incorporate imprecise and vague information and make a decision-making UMS process more realistic. Accordingly, the objective of the paper was to propose a newly developed model that will (considering the integration of various urban mobility subsystems) enable the detection, identification, and ranking of key priorities required for a more holistic approach to UMS planning. The results revealed that the developed integrated model enables acquired areas to be ranked according to priorities, which further allows the development of scenarios. Moreover, the model allows a better understanding of how to search for compromises when one is faced with multi-criteria decision-making and coordination of frequently contradictory goals. A new integrated urban mobility model, as proposed herein, was also successfully tested in a real-life application, which proves its potential for use in sustainable urban mobility planning in a holistic way.

The period of industrialization and modernization has increased energy demands around the world. As with other countries, the Taiwanese government is trying to increase the proportion of renewable energy, especially solar energy resources. Thus, there are many solar power plants built in Taiwan. One of the most important components of a solar power plant is the solar panel. The solar panel supplier selection process is a complex and multi-faceted decision that can reduce the cost of purchasing equipment and supply this equipment on time. In this research, we propose fuzzy MCDM approach that includes fuzzy analytical hierarchy process model (FAHP) and data envelopment analysis (DEA) for evaluation and selection of solar panel supplier for a photovoltaic system design in Taiwan. The main objective of this work is to design a fuzzy MCDM approach for solar panel supplier selection based on qualitative and quantitative factors. In the first step of this research, FAHP is applied to define the priority of suppliers. The AHP combined with fuzzy logic (FAHP) can be used to rank suppliers; however, the disadvantages of the FAHP model is that input data, expressed in linguistic terms, depends on experience of experts and the number of suppliers is practically limited, because of the number of pairwise comparison matrices. Thus, we applied several DEA models for ranking potential suppliers in the final stages. As the result, decision making unit 1 (DMU 1) is the optimal solar panel supplier for photovoltaic system design in Taiwan. The contribution of this research is a new fuzzy MCDM for supplier selection under fuzzy environment conditions. This paper also lies in the evolution of a new approach that is flexible and practical to the decision maker. It provides a useful guideline for solar panel supplier selection in many countries as well as a guideline for supplier selection in other industries.

The application of multiple criteria decision-making methods (MCDM) is aimed at choosing the best alternative out of the number of available versions in the absence of the apparently dominant alternative. One of the two major components of multiple criteria decision-making methods is represented by the weights of the criteria describing the considered process. The weights of the criteria quantitatively express their significance and influence on the evaluation result. The criterion weights can be subjective, i.e., based on the estimates assigned by the experts, and the so-called objective, i.e., those which assess the structure of the data array at the time of evaluation. Several groups of experts, representing the opinions of various interested parties may take part in the evaluation of criteria. The evaluation data on the criterion weights also depend on the mathematical methods used for calculations and the estimation scales. In determining the objective weights, several methods, assessing various properties or characteristics of the data array’s structure, are usually employed. Therefore, the use of the procedures, improving the accuracy of the evaluation of the weights’ values and the integration of the obtained data into a single value, is often required. The present paper offers a new approach to more accurate evaluation of the criteria weights obtained by using various methods based on the idea of the Bayes hypothesis. The performed investigation shows that the suggested method is symmetrical and does not depend on the fact whether a priori or posterior values of the weights are recalculated. This result is the theoretical basis for practical use of the method of combining the weights obtained by various approaches as the geometric mean of various estimates. The ideas suggested by the authors have been repeatedly used in the investigation for combining the objective weights, for recalculating the criteria weights after obtaining the estimates of other groups of experts and for combining the subjective and the objective weights. The recalculated values of the weights of the criteria are used in the work for evaluating the quality of the distant courses taught to the students.

This paper examine the development of railway passenger transport in the European Union countries by using criteria related to the transportation process and the level of economic development of the countries. The study proposes a methodology based on the combination of multicriteria methods. In the first step we determine the indicators to be used in evaluating railway passenger development. As main criteria of the assessment we have chosen social and economic factors, infrastructure factors, factors associated with travel and technological factors. In the second step, using the Fuzzy AHP method, the weights of the criteria and sub-criteria have been calculated. In the third step, we have rated the studied countries by means of the PROMETHEE method. The results show that the factors associated with travel and technological factors have great importance in the ranking of the countries and that, when all factors are taken into account, the countries with the most highly developed railway passenger transport are Germany, Britain and France. The results of the method in the fourth step were compared by applying Cluster analysis. The railway passenger transport in European Union countries have been classified into 5 groups.

Recently, risk assessment has become one of the most challenging issues in the areas of construction and public-private partnerships (PPPs). To address risk assessment issues, various decision-making techniques have been proposed, each with its own specific disadvantages and advantages. This paper investigates step-wise weight assessment ratio analysis (SWARA), complex proportional assessment (COPRAS), fuzzy analytic network process (FANP), fuzzy analytic hierarchy process (FAHP), fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS), simple additive weighting (SAW) and evaluation based on distance from average solution (EDAS) in order to define how various multi-attribute decision-making (MADM) methods compare when used for risk assessment in PPP projects. For this study, 5 risk assessment criteria and 10 types of risk used in Iranian highway PPP projects were selected. Four suitability and applicability tests were used to measure agreement between the rankings derived from the MADM methods. Final results show that all techniques had approximately the same rankings of risk assessment, with the SWARA, COPRAS, and EDAS methods performing slightly better. The findings of this study will help the parties in PPP and construction projects to select the best risk assessment method., This article belongs to the Special Issue Rational Decision Making in Risk Management

[EN] Data processing techniques for Ground Penetrating Radar (GPR) image mining provide essential information to optimize maintenance management of Water Supply Systems (WSSs). These techniques aim to elaborate on radargrams in order to produce meaningful graphical representations of critical buried components of WSSs. These representations are helpful non-destructive evaluation tools to prevent possible failures in WSSs by keeping them adequately monitored. This paper proposes an integrated multi-criteria decision making (MCDM) approach to prioritize various data processing techniques by means of ranking their outputs, namely their resulting GPR image representations. The Fuzzy Analytic Hierarchy Process (FAHP) is applied to weight various evaluation criteria, with the purpose of managing vagueness and uncertainty characterizing experts' judgments. Then, the Elimination Et Choix Traduisant la REalite III (ELECTRE III) method is used to obtain the final ranking of alternatives. A real case study, focusing on a set of four GPR images as outputs of different data processing techniques, is presented to prove the usefulness of the proposed hybrid approach. In particular, the GPR images are ranked according the evaluation of five criteria namely visualization, interpretation, identification of features, extraction of information and affordability. The findings offer a structured support in selecting the most suitable data processing technique(s) to explore WSS underground. In the presented case, two options, namely the variance filter and the subtraction methods, offer the best results. (C) 2018 Elsevier B.V. All rights reserved., Part of this work has been developed under the support of the Universitat Politecnica de Valencia, Valencia (Spain), grant: UPV mobility program for PhD students, awarded to the first author, and of Fundacion Carolina PhD, within its short stage scholarship program awarded to the second author.

Zadnjih su godina u projektiranju i izgradnji građevina organizacije i istraživači usredotočeni na ocjenu inteligentne zgrade. Performanse inteligentnih zgrada (IB) mjere se na temelju karakteristika koje se odnose na IB i stvarnih okolnosti. U ovom se radu koristi teorija fuzzy niza, analitički hijerarhijski postupak (AHP) i analiza podataka grupe (data envelopment analysis - DEA), i nudi integrirana fuzzy AHP-fuzzy DEA (FAHP-FDEA) metoda za ocjenu inteligentne zgrade. Primjenjuje se teorija fuzzy niza za modeliranje nepreciznih i neodređenih podataka ocjenjivačkih kriterija. Budući da su oni od različite važnosti u postupku ocjenjivanja, za određivanje težine kriterija primjenjuje se FAHP. Tada se težina kriterija uključuje u FDEA model kako bi se dobila ocjena performanse inteligentne zgrade. Čistom fuzzy AHP metodom moguće je usporediti samo vrlo ograničen broj alternativa za donošenje odluke dok se predloženom FAHP-FDEA metodom može rangirati ogroman broj alternativa. Razmotrena je analiza slučaja uzetog iz literature da bi se pokazala primjenjivost i učinkovitost predloženog modela FAHP-FDEA. Rezultati su potvrdili da se predloženom metodom dobivaju rezultati u skladu s postojećim metodama u literaturi. Uz to, predloženom se metodom omogućuje da donosioci odluke rezultate donesu u skladu s težnjama., In the recent years, organizations and researchers have been focused on the intelligent building assessment in building design and construction. The performance of intelligent buildings (IBs) is measured based on the IB related characteristics and actual circumstances. This paper utilizes the fuzzy set theory, analytic hierarchy process (AHP), and data envelopment analysis (DEA), and offers an integrated fuzzy AHP-fuzzy DEA (FAHP-FDEA) method for intelligent building assessment. The fuzzy set theory is used to model the imprecise and vague data of the evaluation criteria. Since, the evaluation criteria have different importance in the evaluation process; FAHP is employed to determine the weight of criteria. Then, the weight of criteria is incorporated to a FDEA model to measure the intelligent buildings’ performance. The pure fuzzy AHP method can only compare a very limited number of decision alternatives, while the proposed FAHP-FDEA can rank a huge number of alternatives. A case study taken from the literature is considered to show applicability and effectiveness of the proposed FAHP-FDEA model. The results affirmed that the proposed method provides the consistent results with the existing methods in the literature. In addition, the proposed method enables decision makers to determine the results under different aspiration levels.

The goal of this paper is to compare quality assurance in different contractor contracts by means of multi-attribute decision-making (MADM) and to select the best option. For this investigation, the authors have developed the complex of quality evaluation criteria. During experimental evaluation, the significance of criteria was determined and the expert evaluation of template construction contracts was performed. The complex comparison of contractor contracts was carried out by means of the following MADM methods: Simple Additive Weighting (SAW), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Complex Proportional Assessment (COPRAS) as well as the new Evaluation Based on Distance from Average Solution (EDAS). MADM. method. To determine the weights of criteria, with due consideration of uncertainty of expert evaluation, the Fuzzy Analytic Hierarchy Process (FAHP) method was applied. Evaluation of the data structure was performed by methods for the determination of objective weights: an entropy method and new criteria impact loss (CILOS) and integrated determination of objective criteria weights (IDOCRIW) methods. Expert subjective and objective weights were combined into aggregate weights. Based on the investigation performed, the authors make conclusions regarding possibilities for improving quality assurance in contractor contracts.

Groundwater quality deterioration which originates from excessive pumping caused motivation of the identification of suitable area for groundwater harvesting. In this study, eight quality parameters e.g. Na, Ca, Mg, SO4, TDS, EC, CL and NO3 of Schuler standard along with water level drawdown and water transmissivity coefficient (T) were considered as decision criteria and were calculated using Analytical Hierarchy Process (AHP) method. Then raster data layers of criteria were prepared in GIS tools fuzzified using fuzzy membership function and criteria fuzzy layers decision were created by overlaying of fuzzy raster layers of criteria. As main goal of the paper, final layer of suitable area of water drinking harvest was categorized in five class containing poor, average, fairly good, good and very good levels. The results showed that 2.24, 28.08, 27.86, 28.17 and 13.63 percent of the aquifer area respectively are placed in the mentioned classes. Also a comparison was carried out between modeling results and drinking water wells in the aquifer. Results showed that the eastern parts of the plain have favorable conditions for water drinking exploitation.

In the context of increasing energy demands in Vietnam, and as a result of the limited supply of domestic energy (oil/gas/coal reserves are exhausted), the potential for renewable energy sources in Vietnam is significant. Thus, building wind power plants in Vietnam is necessary. Access to this type of renewable energy not only contributes to society&rsquo, s energy supply but also helps to save energy and reduce environmental pollution. Although some works have reviewed applications of the Multi-Criteria Decision Making (MCDM) model in wind power plant site selection, little research has focused on this problem in a fuzzy environment. This is the reason why a hybrid Fuzzy Analytic Hierarchy Process (FAHP) and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are developed for wind power plant site selection in Vietnam. In the first stages of this research, an FAHP model is proposed for determining the weight of each potential location for building a wind power plant, based on qualitative and quantitative factors. A TOPSIS is applied for ranking all potential alternatives in the final stage. The authors collected data from seven locations, which have good conditions for investment in a wind power plant. The results indicate that Binh Thuan (Binh Thuan Province is located on coast of South Central Vietnam) is the best place for building a wind power plant in Vietnam. The contributions of this work proposed an MCDM approach under fuzzy environments for wind power plant location selection in Vietnam. This paper also resides in the evolution of a new approach that is flexible and practical for a decision-maker. This work also provides a useful guideline for wind power plant location selection in others countries.

The use of third party logistic(3PL) services providers is increasing globally to accomplish the strategic objectives. In the increasingly competitive environment, logistics strategic management requires systematic and structured approach to have cutting edge over the rival. Logistics service provider selection is a complex multi-criteria decision making process; in which, decision makers have to deals with the optimization of conflicting objectives such as quality, cost, and delivery time. In this paper, fuzzy analytic hierarchy process (FAHP) approach based on technique for order preference by similarity to ideal solution (TOPSIS) method has been proposed for evaluating and selecting an appropriate logistics service provider, where the ratings of each alternative and importance weight of each criterion are expressed in triangular fuzzy numbers.

Article history: Received 20 June 2011 Received in revised form August, 2, 2011 Accepted August, 3 2011 Available online 16 August 2011 Decisions related to acceptance or rejection of orders play an important role in companies engaged in make-to-order production. The incoming orders have a specific delivery date by which the customer expects the due date to be met and the order delivered. In some cases the level of input orders exceeds beyond the existing capacity. In such situations the main concern is to decide which orders must be accepted and which ones rejected taking into account the available production capacity. This paper prioritises the input orders according to a comprehensive and systematic multi criteria decision making (MCDM) model. It then proceeds with making decisions to either accept or reject orders according to the calculated prioritises and production constraints. Ultimately the optimum list of orders for acceptance is determined. The proposed model is a combination of two techniques of Fuzzy Analytical Hierarchy Process (FAHP) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). In this model FAHP is used to determine the weights of criteria and TOPSIS is used for prioritizing the orders. Finally the proposed model is tested for its efficiency by application to a real case. © 2012 Growing Science Ltd. All rights reserved

In this paper a new method to improve the inconsistency of pair wise comparison matrices is proposed. To do so, we used Zeshui’s method in fuzzy form. Also we developed a complete fuzzy AHP method by combining Cao’s inconsistency test method, Buckley’s revised AHP method, Chen’s ranking method, and Genetic Algorithm method to calculate the overall priorities

An evaluation method is presented to evaluate the effect of construction enterprises culture development. This paper gives a brief introduction to the connotation and path of construction enterprises culture, also the project-oriented characteristics of it. On this basis, the evaluation index system is given by the literature. Then the disadvantages of AHP are enumerated, and a more effective method of fuzzy analytical hierarchy process (FAHP) is presented, which is proved to be effective by a case.

This paper investigates a greenhouse microclimatic environment controlled by a mobile measuring station with the aim of improving performance by using wireless sensor networks (WSN) technology. The algorithms for the mobile measuring station that perform navigation tasks are called Bug algorithms. The existing potential field method based algorithms are improved with an RSSI signal propagation model and implemented on a two-wheel driven robot developing system and their performances are measured and analyzed. The implementation part is done on Boe-Bot equipped with SunSPOT enabling the wireless control ability. The control surface is generally made with LabVIEW and a relational database. Control strategy selection system is supported by Fuzzy Analytic Hierarchy Process (FAHP). Navigation of the mobile measuring robot can be done manually, relying on the visual data from the robot's camera, or it can be switched to automatic mode where the developed algorithm does the navigation job. Mobile robot navigation is based on the potential field method considering a wide range of energy-aware parameters.

The aim of the research is to develop a fuzzy decision making model for the selection of a suitable multimedia application for learning using subjective judgments of decision makers. The proposed approach is based on FAHP and TOPSIS methods. FAHP method is first used to determine the weight criteria for decision-making, and then with TOPSIS method order of multimedia applications is defined. Criterias are defined according to the Bloom's digital taxonomy. In this paper empirical study of the selection of multimedia applications for learning is shown and discussed.

A lot of computer-based methods have been developed to assess the evacuation capability (EC) of high-rise buildings. Because softwares are time-consuming and not proper for on scene applications, we adopted two methods, fuzzy analytic hierarchy process (FAHP) and technique for order preference by similarity to an ideal solution (TOPSIS), for EC assessment of a high-rise building in Jinan. The EC scores obtained with the two methods and the evacuation time acquired with Pathfinder 2009 for floors 47-60 of the building were compared with each other. The results show that FAHP performs better than TOPSIS for EC assessment of high-rise buildings, especially in the aspect of dealing with the effect of occupant type and distance to exit on EC, tackling complex problem with multi-level structure of criteria, and requiring less amount of computation. However, both FAHP and TOPSIS failed to appropriately handle the situation where the exit width changes while occupants are few., {"references":["UNFPA, State of world population 2010. New York: UNFPA, 2010.","S. Gwynne, E. R. Galea, M. Owen, P. J. Lawrence, and L. Filippidis, \"A\nreview of the methodologies used in the computer simulation of\nevacuation from the built environment,\" Build. Environ., vol. 34, pp.\n741-749, 1999.","S. Gwynne, E. R. Galea, M. Owen, and L. Filippidis, \"A systematic\ncomparison of model predictions produced by the buildingEXODUS\nevacuation model and the Tsukuba pavilion evacuation data,\" J. Appl.\nFire Sci., vol. 7, no. 3, pp. 235-266, 1998.","P. A. Thompson, E. W. Marchant, \"A computer-model for the evacuation\nof large building populations,\" Fire Safety J., vol. 24, no. 2, pp. 131-148,\n1995.","S. M. Lo, Z. Fang, P. Lin, G. S. Zhi, \"An evacuation model: the SGEM\npackage,\" Fire Safety J., vol. 39, no. 3, pp. 169-190, 2004.","J. P. Yuan, Z. Fang, Y. C. Wang, S. M. Lo, P. Wang, \"Integrated network\napproach of evacuation simulation for large complex buildings,\" Fire\nSafety J., vol. 44, no. 2, pp. 266-275, 2009.","T. L. Saaty, The analytic hierarchy process. New York: McGraw-Hill,\n1980.","L. A. Zadeh, \"Fuzzy sets,\" Inform. Control, vol. 8, pp. 338-353. 1965.","R. R. Yager, S. Ovchinnikov, R. M. Tong, H. T. Nguyen, L.A. Zadeh:\nSelected Papers on Fuzzy Sets and Applications. New York: John Wiley\n& Sons, 1987.\n[10] P. J. M. Van Laarhoven, W. Pedrycz, \"A fuzzy extension of Saary's\npriority theory,\" Fuzzy Set Syst., vol. 11, no. 3, pp. 229-241, 1983.\n[11] T. L. Saaty, \"How to make a decision-the analytic hierarchy process,\"\nInterfaces, vol. 24, no. 6, pp. 19-43, 1994.\n[12] C. L. Hwang, and K. Yoon, Multiple attribute decision making: Methods\nand applications. New York: Springer-Verlag, 1981.\n[13] L. Shi, Q. Y. Xie, X. D. Cheng, L. Chen, Y. Zhou, and R. F. Zhang,\n\"Developing a Database for Emergency Evacuation Model,\" Build.\nEnviron., vol. 44, pp. 1724-1729, 2009.\n[14] K. Togawa, 1955. Study on Fire Escapes Based on the Observation of\nMultitude Currents. Japanese Building Research Institute Report 14,\nTokyo.\n[15] C. Kahraman, S. Cevik, N. Y. Ates, and M. Gulbay, \"Fuzzy multi-criteria\nevaluation of industrial robotic systems,\" Comput. Ind. Eng., vol. 52, pp.\n143-168, 2007.\n[16] J. W. Wang, C. H. Cheng, K. C. Huang, \"Fuzzy hierarchical TOPSIS for\nsupplier selection,\" Appl. Soft Comput., vol. 9, pp. 377-386, 2009."]}

The aim objective of this study is to model mining method selection problem for a real world case in Angouran mine which is one of the major zinc producers in Iran. According to many problems of ore body extraction are direct or indirect depend on underground mining method, this issue is one of the most critical decisions in the design stage of mine that should be made. A number of the evaluation criteria that often are in conflicting with each other exist for evaluating feasible mining methods. Therefore, the problem of mining method selection is a multi-criteria decision making (MCDM) issue.On the other hand, according to the sophisticated structure of the problem, imprecise data, less of information, and inherent uncertainty, the usage of the fuzzy sets can be useful. In this paper an integrated model based on fuzzy analytic hierarchy process (FAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) is developed. FAHP is applied to determine the relative weights of the evaluation criteria for mining method selection that these weights are inserted to the FTOPSIS technique to rank the alternatives and select the most appropriate alternative. The study was followed by the sensitivity analysis of the results. The results of this study demonstrate the efficiency, capability, and robustness of the proposed model, which can be applied to different types of sophisticated problems in reality., Cilj ovog rada je izvođenje efikasnog i primjenjivog modela odabira najbolje proizvodne tehnike na primjeru Angouran rudnika koji je jedan od glavnih proizvođača cinka u Iranu. Proizvodne tehnike ekstrakcije ruda su izravno ili neizravno ovisne o izboru tehnika izvlačenja ruda, jednog od najkritičnijih pitanja u odlučivanju u fazi projektiranja rudnika koji bi trebao biti izrađen. Broj evaluacijskih kriterija često su u sukobu jedni s drugima pri odabiru i ocjeni prihvatljive proizvodne (rudarske) metode i tehnike. Dakle, problem odabira prihvatljive proizvodne rudarske metode u praksi je problem odabira multi-kriterijskog odlučivanja (MCDM). S druge strane, s obzirom na složenost i strukturu problema, nepreciznih podataka, manjkavost informacija, a time i inherentnu nesigurnost, korištenje fuzzy tehnika može biti od iznimne koristi. U ovom radu integrirani model koji se temelji fuzzy analitičkoj hijerarhiji procesa (FAHP) i fuzzy tehnikama za redom preferencija po sličnosti idealnog rješenja (FTOPSIS) je razvijen i prezentiran. FAHP se primjenjuje za određivanje relativne težine kriterija za ocjenu najbolje proizvodne tehnike pri ekstrakciji ruda u odnosu na ostale dostupne alternativne proizvodne tehnike. Rezultati istraživanja rada testirani su analizom osjetljivosti rezultata. Rezultati ovog istraživanja pokazuju učinkovitost, sposobnost i robusnost predloženog modela izbora proizvodnih tehnika, koji se mogu primijeniti na različite vrste složenih problema u stvarnom životu.

The supplier selection is critical towards the success of a company. This paper compares four different methods to support decision makers in selecting the most appropriate supplier. When using Fuzzy logic, the importance of each criterion gets influenced by the level of decomposition in the hierarchical model. Fuzzy logic does not have the capability to measure the level of consistency in the judgments provided by a decision maker. On the other hand, analytic hierarchy process (AHP) cannot capture subjectivity (or fuzziness) of human judgements as the verbal assessments are converted into crisp values. Fuzzy analytic hierarchy process (FAHP) is a merger of the two methods, Fuzzy logic and the Analytic Hierarchy Process (AHP), which inherits the advantages of both and, therefore, addresses the above mentioned problems. The FAHP method is useful in identifying a suitable supplier and to evaluate its performance as demonstrated in the described case study.

The selection of an appropriate resilience investment strategy to optimize the operational efficiency of a seaport is a challenging task given that many criteria need to be considered and modelled under an uncertain environment. The design of such a complex decision system consists of many subjective and imprecise parameters contained in different quantitative and qualitative forms. This paper proposes a fuzzy multi-attribute decision making methodology for the selection of an appropriate resilience investment strategy in a succinct and straightforward manner. The decision support model allows for a collaborative modelling of the system by multiple analysts in a group decision making process. Fuzzy analytical hierarchy process (FAHP) was utilized to analyse the complex structure of the system to obtain the weights of all the criteria while fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) was employed to facilitate the ranking process of the resilience strategies. Given that it is often financially difficult to invest in all the resilience strategies, it is envisaged that the proposed approach could provide decision makers with a flexible and transparent tool for selecting appropriate resilience strategies aimed at increasing the resilience of seaport operations.

The aim of this paper is developing a new hierarchical model to evaluate and rank the sawability (power consumption) of carbonate rock with the use of effective and major criteria, and simultaneously taking subjective judgments of decision makers into consideration. The proposed approach is based on the combination of Fuzzy Analytic Hierarchy Process (FAHP) method with TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods. FAHP is used for determining the weights of the criteria by decision makers, and then rankings of carbonate rocks are determined by TOPSIS. The proposed method is applied for Iranian ornamental stone to evaluate the power consumption in rock sawing process. A variety of two groups of carbonate rocks (7 types) were sawn, using a fully-instrumented laboratory cutting rig at different feed rate (200, 300, 400 cm min −1 ) at constant peripheral speed (1770 rpm) and depth of cut (35 mm). During the sawing trials, the ampere and power consumption were monitored and calculated as performance characteristics of the saws. The results of the sawing trials (power consumption) were used to verify the result of the applied approach for ranking the carbonate rock sawability. It was concluded that the sawability of carbonate rocks can reliably be ranked, using the developed approach.

In this paper, SWOT analysis and fuzzy Analytic Hierarchy Process (FAHP) have been employed to structure and determine the importance of all identified alternatives for developing strategic management in a local district heating plant in Serbia. Weaknesses are identified as drivers of technological slowdown in the plant. The outcome of the prioritization highlights the importance of solving challenges regarding weaknesses by relying on a variety of opportunities that emerge in the environment. The potential of restoring the equipment of the district heating plant is found to be the most important alternative for strategic development.