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Abstract: This paper proposes a new approach to design optimal double auction mechanism with multi-objectives. In the optimal double auction mechanism, optimality is represented as multi-objectives to maximize the expected total revenue of sellers and buyers respectively at the same time. We give representation of allocation rules and payment rules of the optimal double auction mechanism that satisfies incentive compatibility, individual rationality, market clearing, and budget-balanced restrictions. Finally, we present a numerical example to demonstrate the function of the developed optimal double auction mechanism and its efficiency. [Copyright &y& Elsevier]

Abstract: This paper compares the effectiveness of five state-of-the-art multiobjective evolutionary algorithms (MOEAs) together with a steady state evolutionary algorithm on the mean–variance cardinality constrained portfolio optimization problem (MVCCPO). The main computational challenges of the model are due to the presence of a nonlinear objective function and the discrete constraints. The MOEAs considered are the Niched Pareto genetic algorithm 2 (NPGA2), non-dominated sorting genetic algorithm II (NSGA-II), Pareto envelope-based selection algorithm (PESA), strength Pareto evolutionary algorithm 2 (SPEA2), and e-multiobjective evolutionary algorithm (e-MOEA). The computational comparison was performed using formal metrics proposed by the evolutionary multiobjective optimization community on publicly available data sets which contain up to 2196 assets. [Copyright &y& Elsevier]

Abstract: Decision-making problems often involve a complex decision-making process in which multiple requirements and uncertain conditions have to be taken into consideration simultaneously. We are often required to deal with uncertainty, subjectiveness and imprecise data, which are represented by fuzzy data. In this paper, we consider the ideal solution and the anti-ideal solution and assess each alternative in terms of distance as well as similarity to the ideal solution and the anti-ideal solution. To minimize the error, the normalization of fuzzy data is carefully avoided. To get greater accuracy in ranking fuzzy rating, we use the latest and advanced similarity measure. Distance and similarity measures for fuzzy numbers are used and aggregation is guided by the decision rules in order to construct decision function. Further, OWA operators with maximal entropy are used to aggregate across all criteria and the overall score of each alternative is determined The proposed method is more flexible in modeling the decision maker’s preferences and more appropriate and effective to handle multicriteria problems of considerable complexity. [Copyright &y& Elsevier]

Abstract: Recently, resolving the problem of evaluation and ranking the potential suppliers has become as a key strategic factor for business firms. With the development of intelligent and automated information systems in the information era, the need for more efficient decision making methods is growing. The VIKOR method was developed to solve multiple criteria decision making (MCDM) problems with conflicting and non-commensurable criteria assuming that compromising is acceptable to resolve conflicts. On the other side objective weights based on Shannon entropy concept could be used to regulate subjective weights assigned by decision makers or even taking into account the end-users’ opinions. In this paper, we treat supplier selection as a group multiple criteria decision making (GMCDM) problem and obtain decision makers’ opinions in the form of linguistic terms. Then, these linguistic terms are converted to trapezoidal fuzzy numbers. We extended the VIKOR method with a mechanism to extract and deploy objective weights based on Shannon entropy concept. The final result is obtained through next steps based on factors R, S and Q. A numerical example is proposed to illustrate an application of the proposed method. [Copyright &y& Elsevier]

Abstract: The frequently used methods of handling optimism and pessimism in multiple criteria decision analysis are Hurwicz’s and Yager’s approaches. Despite their wide usage, a critical issue has been raised about unidimensionality. Numerous psychological researches and empirical findings have convincingly supported that optimism and pessimism do not represent opposite poles on a single, bipolar dimension, but they are conceived as two partially independent dimensions instead. The focus of this paper is a two-dimensional approach by adequately employing the degrees of membership and non-membership based on Atanassov fuzzy sets. This study develops optimistic and pessimistic estimations with several fuzzy point operators to draw the influences of optimism and pessimism on multicriteria decision making for the sake of a better fit than the unidimensional model. Given a typology from empirical grounds, the appropriate point operators specific to each type are suggested to identify adaptational outcomes. Base upon a series of new score functions, a useful method for multiple criteria decision analysis is provided to efficiently facilitate decision analysis with a multimeasure approach. Feasibility and effectiveness of the proposed methods are illustrated by a practical example. [Copyright &y& Elsevier]

Abstract: In recent decades, intuitionistic fuzzy sets have been applied to many different fields; however, few current studies have used the ELECTRE method to solve multi-criteria decision-making problems with intuitionistic fuzzy information. The purpose of this paper is to develop a new method, the intuitionistic fuzzy ELECTRE method, for solving multi-criteria decision-making problems. Atanassov’s intuitionistic fuzzy set (A-IFS) characteristics are simultaneously concerned with the degree of membership, degree of non-membership, and intuitionistic index, and people can use A-IFS to describe uncertain situations in decision-making problems. We use the proposed method to rank all alternatives and determine the best alternative. The proposed method can also use imperfect or insufficient knowledge of data to deal with decision-making problems. Finally, two practical examples are given that illustrate the procedure of the proposed method. [Copyright &y& Elsevier]

Abstract: Due to the increasing competition of globalization, selection of the most appropriate personnel is one of the key factors for an organization’s success.The importance and complexity of the personnel selection problem call for the method combining both subjective and objective assessments rather than just subjective decisions. The aim of this paper is to develop a new method for solving the decision making process. An intuitionistic fuzzy multi-criteria group decision making method with grey relational analysis (GRA) is proposed. Intuitionistic fuzzy weighted averaging (IFWA) operator is utilized to aggregate individual opinions of decision makers into a group opinion. Intuitionistic fuzzy entropy is used to obtain the entropy weights of the criteria. GRA is applied to the ranking and selection of alternatives. A numerical example for personnel selection is given to illustrate the proposed method finally. [Copyright &y& Elsevier]

Abstract: Nowadays, as in all other organizations, the amount of waste generated in the health-care institutions is rising due to their extent of service. Medical waste management is a common problem of developing countries including Turkey, which are becoming increasingly conscious that health-care wastes require special treatment. Accordingly, one of the most important problems encountered in Istanbul, the most crowded metropolis of Turkey, is the disposal of health-care waste (HCW) from health-care institutions. Evaluating HCW disposal alternatives, which considers the need to trade-off multiple conflicting criteria with the involvement of a group of experts, is a highly important multi-criteria group decision making problem. The inherent imprecision and vagueness in criteria values concerning HCW disposal alternatives justify the use of fuzzy set theory. This paper presents a fuzzy multi-criteria group decision making framework based on the principles of fuzzy measure and fuzzy integral for evaluating HCW treatment alternatives for Istanbul. In group decision making problems, aggregation of expert opinions is essential for properly conducting the evaluation process. In this study, the ordered weighted averaging (OWA) operator is used to aggregate decision makers’ opinions. Economic, technical, environmental and social criteria and their related sub-criteria are employed to assess HCW treatment alternatives, namely “incineration”, “steam sterilization”, “microwave”, and “landfill”. A comparative analysis is presented using another classical operator to aggregate decision makers’ preferences. [Copyright &y& Elsevier]

Abstract: The purpose of this paper is to develop a new approach for measuring the decision makers’ weights in group decision making setting, in which the decision information, provided by multiple decision makers, is expressed in interval-valued intuitionistic fuzzy numbers. There are two key issues being addressed in this approach. The first one is to develop an ideal decision of group, which is the mean of group decision. The second one is to select the similarity measure between each individual decision and the ideal decision according to the idea of the TOPSIS of . A numeric example is also given to clarify the developed approach and to demonstrate its effectiveness. [Copyright &y& Elsevier]

Abstract: In this paper, we introduce the expected values for intuitionistic trapezoidal fuzzy numbers and presented a handling method for intuitionistic trapezoidal fuzzy multicriteria decision-making problems, in which the preference values of an alternative on criteria and the weight values of criteria take the form of intuitionistic trapezoidal fuzzy numbers. Simple and exact formulas are proposed to determine the expected weight values of the criteria for an alternative and weighted expected value for an alternative. Therefore, the expected value method is extended for ranking alternatives and the most desirable one(s) can be selected according to the weighted expected values. Finally, an illustrative example shows that the proposed method is simple and effective. [Copyright &y& Elsevier]

Abstract: The aim of this paper is to investigate the multiple attribute decision making problems with intuitionistic fuzzy information, in which the information about attribute weights is incompletely known, and the attribute values take the form of intuitionistic fuzzy numbers. In order to get the weight vector of the attribute, we establish an optimization model based on the basic ideal of traditional gray relational analysis (GRA) method, by which the attribute weights can be determined. For the special situations where the information about attribute weights is completely unknown, we establish another optimization model. By solving this model, we get a simple and exact formula, which can be used to determine the attribute weights. Then, based on the traditional GRA method, calculation steps for solving intuitionistic fuzzy multiple attribute decision-making problems with incompletely known weight information are given. Furthermore, we have extended the above results to an interval-valued intuitionistic fuzzy environment and developed modified GRA method for interval-valued intuitionistic fuzzy multiple attribute decision-making with incompletely known attribute weight information. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness. [Copyright &y& Elsevier]

Abstract: In today’s market, flexibility has received much concern of companies because of its important role in responding to the ever-changing environment. Most of the research in the literature on flexibility investment is focused on one objective, i.e. profit maximization. However, more and more company managers and customers pay much attention to another objective, i.e. production efficiency maximization. There is a need to develop flexibility investment strategy by considering these two objectives simultaneously. In this paper, we propose a multi-objective decision making method to derive the optimal flexibility investment strategy. Both efficiency and profit are taken into account as objectives when making flexibility investment decisions. The proposed method is a hierarchical method which composes of two-level models. Based on the characteristics of the models, a guideline is presented to help managers conveniently find out the optimal flexibility investment strategy. Simulation experiments are performed to verify the validity of the proposed models and guideline. The results of the simulation illustrate that the flexibility configuration obtained by following the guideline leads to benefit very close to total flexibility configuration, and much higher than 2-Skill Chain configuration; while the cost much less than total flexibility configuration, and even less than 2- Skill Chain configuration. [Copyright &y& Elsevier]

Abstract: Supplier selection problem is a multi-criteria decision making problem which includes both qualitative and quantitative factors. In the selection process many criteria may conflict with each other, therefore decision-making process becomes complicated. In this paper, we propose a compensatory fuzzy approach to solve multi-objective linear supplier selection problem with multiple-item (MLSSP-MI) by using Werners’ “fuzzy and” (μand ) operator. The compromise solutions obtained by using “fuzzy and” (μand ) operator are both compensatory and strongly efficient for our MLSSP-MI. To our knowledge, combining compensatory (μand ) operator with MLSSP-MI has not been published up to now. Our compensatory fuzzy approach was explained on a case study. [Copyright &y& Elsevier]

Abstract: Fuzzy mathematical programming is a main approach of multi-objective decision making, which prepares the decision makers to obtain the solution that satisfies his/her preference. In this paper, a fuzzy weighted max–min model for a mean–absolute deviation portfolio selection problem with real features is represented. To solve the resulted models, a hybrid genetic algorithm is proposed. An empirical study based on 75 assets of New York stock exchange (NYSE) is considered for in sample and out of sample analysis to illustrate the efficiency of the proposed model. The results show the high performance of fuzzy portfolios comparing with the performance of crisp portfolios and S&P 500 index. [Copyright &y& Elsevier]

Abstract: Multiple response problems include three stages: data gathering, modeling and optimization. Most approaches to multiple response optimization ignore the effects of the modeling stage; the model is taken as given and subjected to multi-objective optimization. Moreover, these approaches use subjective methods for the trade off between responses to obtain one or more solutions. In contradistinction, in this paper we use the Prediction Intervals (PIs) from the model building stage to trade off between responses in an objective manner. Our new method combines concepts from the goal programming approach with normalization based on negative and positive ideal solutions as well as the use of prediction intervals for obtaining a set of non-dominated and efficient solutions. Then, the non-dominated solutions (alternatives) are ranked by the TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) approach. Since some suggested settings of the input variables may not be possible in practice or may lead to unstable operating conditions, this ranking can be extremely helpful to Decision Makers (DMs). The consideration of statistical results together with the selection of the preferred solution among the efficient solutions by Multiple Attribute Decision Making (MADM) distinguishes our approach from others in the literature. We also show, through a numerical example, how the solutions of other methods can be obtained by modifying the relevant approach according to the DM’s requirements. [Copyright &y& Elsevier]

Abstract: In this paper, we propose a co-evolutionary immune algorithm for the multi-criteria decision making (MCDM) model, and use the model to solve the large scale garment matching problem. Size fitting problem is a main obstacle to large scale garment sales and online sales because it is difficult to find the fit garments by the general size information. This study regards the fit garment matching problem as a MCDM model with the constraints of size satisfaction. An immune co-evolutionary algorithm is used to search the fit garments from the candidate garments in the stock. The garments in the stock are taken as antibodies and the customer request as antigen. The concepts of ideal garment and loose garment are virtual garment to model the customer request. Two affinity measures including dominance affinity and distance affinity are defined to represent the similarity of antibody to antibody and that of antibody to antigen. Correspondingly, the fit garments are chosen by two methods: the Pareto optimal garments by the MCDM solving algorithm, and the optimal garments with the minimal distance affinity to the ideal garments. An evaluation model on garments is proposed to evaluate the fit garments by the affinity measures. Based on the experiment data from the effective study of detail factors of female trousers, the proposed model and algorithm demonstrate to be a feasible and effective attempt aiming at a valuable problem and provide the key tool for garment store sale system or online garment order system to support accurate garment size matching. [Copyright &y& Elsevier]

Abstract: How to measure the adaptation complexity effectively is an open issue in natural or artificial systems. In this paper, some essential characteristics of adaptation in evolvable systems and the importance/complexity of constructing multi-objective fitness functions in evolutionary computation are analyzed. Based on the authors’ previous work on single-objective normalization, a general method is put forward for multi-objective decision making and optimization with its key idea of decomposing the process of constructing fitness functions into their basic units (classes). Then, the issues of determining the corresponding mathematical models and their parameters as well as the issue of integrating all the fitness functions are discussed. Variable weights/objective synthesis is also briefly discussed. A technique in multi-input–multi-output control systems is illustrated to show the usefulness of the method. [Copyright &y& Elsevier]

Abstract: Customer relationship management (CRM) is a multi-perspective business paradigm which aims maximizing the benefits gained from relationships with customers. The aim of this paper is to compare the CRM performances of e-commerce firms using a multiple criteria decision making (MCDM) approach. Analytical network process (ANP) is a MCDM methodology which can take the inner and outer dependencies among multiple criteria into consideration. As there are dependencies among CRM performance evaluation criteria, ANP is used for comparing the CRM performances of the e-commerce firms under consideration. A sensitivity analysis also provided in order to monitor the robustness of the proposed ANP framework to changes in the weights of evaluation criteria. To the authors’ knowledge, this will be the first study which evaluates CRM performance using ANP. [Copyright &y& Elsevier]

Abstract: This paper aims to develop a benchmarking framework that evaluates the cold chain performance of a company, reveals its strengths and weaknesses and finally identifies and prioritizes potential alternatives for continuous improvement. A Delphi-AHP-TOPSIS based methodology has divided the whole benchmarking into three stages. The first stage is Delphi method, where identification, synthesis and prioritization of key performance factors and sub-factors are done and a novel consistent measurement scale is developed. The second stage is Analytic Hierarchy Process (AHP) based cold chain performance evaluation of a selected company against its competitors, so as to observe cold chain performance of individual factors and sub-factors, as well as overall performance index. And, the third stage is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based assessment of possible alternatives for the continuous improvement of the company’s cold chain performance. Finally a demonstration of proposed methodology in a retail industry is presented for better understanding. The proposed framework can assist managers to comprehend the present strengths and weaknesses of their cold. They can identify good practices from the market leader and can benchmark them for improving weaknesses keeping in view the current operational conditions and strategies of the company. This framework also facilitates the decision makers to better understand the complex relationships of the relevant cold chain performance factors in decision-making. [Copyright &y& Elsevier]

Abstract: TOPSIS is one of the major techniques in dealing with multiple criteria decision making (MCDM) problems, and Belief Structure (BS) model and Fuzzy BS model have been used successfully for uncertain MCDM with incompleteness, impreciseness or ignorance. In this paper, the TOPSIS method with Fuzzy BS model is proposed to solve Group Belief MCDM problems. Firstly, the Group Belief MCDM problem is structured as a fuzzy belief decision matrix in which the judgments of each decision maker are described as Fuzzy BS models, and then the Evidential Reasoning approach is used for aggregating the multiple decision makers’ judgments. Subsequently, the positive and negative ideal belief solutions are defined with the principle of TOPSIS. In order to measure the separation from the ideal belief solutions, the concept and algorithm of Belief Distance Measure are introduced to compare the difference between Fuzzy BS models. Using the Belief Distance Measure, the relative closeness and ranking index can be calculated for ranking the alternatives. A numerical example is finally given to illustrate the proposed method. [Copyright &y& Elsevier]

Abstract: Allocating orders to suppliers is of a great importance in managing the supply chain. This process comes after supplier selection and evaluation. Having selected the qualified vendors, the manager will examine the performance of each one and evaluate the individual vendor. According to the results of periodic evaluations, the manager allocates orders to suppliers. Splitting orders among suppliers is so important that it may influence the efficiency of the whole chain. In this paper, we propose a fuzzy multi-criterion model for organizing the process of assigning orders to suppliers. We adopt a fuzzy approach in order to overcome the vagueness of the information due to the uncertainty of them. MCDM methods are used to allocate suitable shares of orders to the best possible suppliers. Different from previous works, we discuss this problem over a multi-period time horizon; namely, the model leads to solutions which optimize the order in both the whole year and the fractional periods of a year. A fuzzy linear programming model is developed to optimize the price, quality and risk objectives and satisfy constraints like logistics costs, suppliers′ capacity, supply chain demand, risk, etc. A numerical example comes to validate our proposed model. [Copyright &y& Elsevier]

Abstract: Trust plays an important role in the operation and management of virtual teams. It is also a foundation of the cooperation between members. In the operation of a virtual team, trust estimation is a very significant issue to know about the trustworthiness of each member and cooperation situations between members. The purpose of this paper is to propose a decision support method for estimating the trust level. A trust estimation framework with two dimensions of reputation and collaboration is developed. From this, a fuzzy multiattribute decision analysis (MADA) approach based on the 2-tuple fuzzy linguistic representation model is proposed to measure the performances on reputation and collaboration. By the measurements of the performances, the trust level of each member and the virtual team can be identified so as to improve the management of the virtual team. Furthermore, a Web-based trust estimation system (WTES) is designed and developed to support the activities of trust estimation in a virtual team. Finally, an application is provided to illustrate the applicability of the proposed decision support method. [Copyright &y& Elsevier]

Abstract: This paper presents Multi Attribute Decision Making (MADM) based methodology for evaluation and selection of a mechatronic system. An exhaustive list of attributes which influence the structure and performance of a mechatronic system are identified. An attribute based coding scheme for identification and differentiation of mechatronic systems is developed. A three stage selection procedure is proposed for optimal selection of a mechatronic system. In the first stage, large numbers of available mechatronic systems are converged to a manageable number using elimination search. Second stage, a matrix for storing all the information pertaining to a mechatronic system alternative is proposed. In the third stage, all the mechatronic systems are ranked according the Euclidian distance of mechatronic system from best possible and worst solutions. Two visual methods namely linear graph and spider chart are proposed for ranking of mechatronic systems. An illustrative example explaining the implementation procedure of proposed methodology is discussed at the end. This methodology is useful for industries in selection of a mechatronic system and also useful for any customer in selection of an optimal mechatronic product. [Copyright &y& Elsevier]

Abstract: In this paper, we focus on the vendor selection problem (VSP) for material supply in large-scale water conservancy and hydropower construction projects, and establish a corresponding model to solve this problem. After stating the problem, we introduce some basic knowledge of level-2 fuzzy sets and the way to transform them to normal fuzzy sets. Then we use the CCP model to handle the bifuzzy objective functions and constraints, based on a series of preparations, we transform the multi-objective integer model under bifuzzy environment into a deterministic model, then use particle swarm optimization (PSO) to solve this problem. The model is illustrated with an actual application to construction material supply. [Copyright &y& Elsevier]

Abstract: Supply chain management allows modern enterprises to relax their own capacities and produce in a more flexible manner for diversified consumer demands. However, for an enterprise with divergent supply chain (DSC) and multiple product lines, to plan the production allocation for higher competitive advantage in the risky global market is a challenging problem. The existing literature still has not address this problem very well. This paper is aimed to treat this problem by using an integrated approach of activity based costing (ABC) and management, five forces analysis, risk and value-at-risk analysis, decision making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), and fuzzy goal programming (FGP). The proposed model can effectively incorporate the key factors of precise costing, managerial constraints, competitive advantage analysis, and risk management into DSC forecasting and multi-objective production planning. A case study of a consumer-oriented cell phone DSC is also presented. The sensitivity analysis shows that identifying and relaxing crucial constraints can play an important role in DSC planning for higher competitive advantage and lower risk. [Copyright &y& Elsevier]

Abstract: Supplier selection is a multi-criterion decision making problem under uncertain environments. Hence, it is reasonable to hand the problem in fuzzy sets theory (FST) and Dempster Shafer theory of evidence (DST). In this paper, a new MCDM methodology, using FST and DST, based on the main idea of the technique for order preference by similarity to an ideal solution (TOPSIS), is developed to deal with supplier selection problem. The basic probability assignments (BPA) can be determined by the distance to the ideal solution and the distance to the negative ideal solution. Dempster combination rule is used to combine all the criterion data to get the final scores of the alternatives in the systems. The final decision results can be drawn through the pignistic probability transformation. In traditional fuzzy TOPSIS method, the quantitative performance of criterion, such as crisp numbers, should be transformed into fuzzy numbers. The proposed method is more flexible due to the reason that the BPA can be determined without the transformation step in traditional fuzzy TOPSIS method. The performance of criterion can be represented as crisp number or fuzzy number according to the real situation in our proposed method. The numerical example about supplier selection is used to illustrate the efficiency of the proposed method. [Copyright &y& Elsevier]

Abstract: This paper proposes a Fuzzy Group Analytical Hierarchy Process approach for assessing the quality of software, with judgments by a group of experts at different levels. The international standard of software quality attributes, ISO/IEC9126-1:2001 which comprises of 6 criteria with 27 subcriteria, is applied as the attributes of software quality. Regarding the prioritization method, the modified fuzzy Logarithmic Least Squares Method (LLSM) is applied to derive the importance weight vectors. The Fuzzy Prioritization Programming for Direct Rating Scales (FPP-DRS) on the basis of the modified fuzzy LLSM and the rescaling functions is proposed to design the direct rating scales in fuzzy number. The Fuzzy Synthesis Programming for Absolute Measurement (FSPAM) including Integrated Fuzzy Scores of Individual Expert (IFSIE) and Group Integrated Fuzzy Score (GIFS) is proposed to aggregate the criteria values from various experts. The proposed approach can help a group of various experts including developers, testers and purchasers, to measure the level of the software quality of the in-house development or the third party development. [Copyright &y& Elsevier]

Abstract: As the IC (integrated circuit) industry migrates to the System-on-Chip (SOC) era, the SOC design service industry is emerging. Meanwhile, in the past decade, the emergence of Internet has changed the high technology marketing approaches while e-commerce has already become one of the most efficient marketing channels. Thus, most leading SOC design service firms tried to leverage novel e-commerce business models to provide better services including online silicon intellectual property (SIP) sourcing, transactions, integration, etc. to assist customers in enhancing their innovation competences to shorten their time to market and thus, time to money. However, defining appropriate e-business models for commercializing new SIPs or SOC design services is not easy for both aspects of technology as well as business development. On one hand, from the aspect of technology, the technical site R&D or production managers are familiar with SOC technologies while do not really understand the needs of customers’ over the Internet. On the other hand, from the aspect of business development, the sales or marketing managers may be familiar with online customers’ needs, wants as well as demands while are unfamiliar to SOC technology developments. To overcome the above mentioned problems, an appropriate e-business model definition framework can overcome this cognitive gap and maximize the value-added of online SOC design services. In this paper, a novel analytic framework based on the concept of design service customers’ competence set expansions by leveraging high technology service firms’ capabilities and resources as well as novel multiple criteria decision making (MCDM) techniques, will be proposed. The framework being proposed can be leveraged by the design service firms to define an appropriate e-business model for possible SIP or design service businesses. Based on the proposed MCDM framework, an empirical study of an SIP commercialization e-business model definition inside an SIP Mall, an SIP e-commerce mechanism being operated by a SOC design service firm, will be provided for verifying the effectiveness of this novel analytic framework. The feasibility of the proposed framework in the real world can be verified by the empirical study. In the future, the novel MCDM framework can be applied to novel e-business model definitions in the SOC design service or other high technology industries. [Copyright &y& Elsevier]

Abstract: This paper aims to develop a combination of Taguchi and fuzzy TOPSIS methods to solve multi-response parameter optimization problems in green manufacturing. Electrical Discharge Machining (EDM), a commonly used non-traditional manufacturing process was considered in this study. A decision making model for the selection of process parameters in order to achieve green EDM was developed. An experimental investigation was carried out based on Taguchi L9 orthogonal array to analyze the sensitivity of green manufacturing attributes to the variations in process parameters such as peak current, pulse duration, dielectric level and flushing pressure. Weighing factors for the output responses were determined using triangular fuzzy numbers and the most desirable factor level combinations were selected based on TOPSIS technique. The model developed in this study can be used as a systematic framework for parameter optimization in environmentally conscious manufacturing processes. [Copyright &y& Elsevier]

Abstract: This paper presents a hybrid fuzzy model for group Multi Criteria Decision Making (MCDM). A modified fuzzy DEMATEL model is presented to deal with the influential relationship between the evaluation criteria. The modified DEMATEL captures such relationship and divides the criteria into two groups, particularly, the cause group and the effect group. The cause group has an influence on the effect group where such influence is used to estimate the criteria weights. In addition, a modified TOPSIS model is proposed to evaluate the criteria against each alternative. Here, a fuzzy distance measure is used in which the distance from the Fuzzy Positive Ideal Solution (FPIS) and Fuzzy Negative Ideal Solution (FNIS) are calculated. The resulted distances were used to calculate the similarity to Ideal and Anti-ideal points. Later, an optimal membership degree (closeness coefficient) of each alternative is computed to estimate to which extent an alternative belongs to both FPIS and FNIS. The closer the degree of membership to FPIS and the farther from FNIS the more preferred the alternative. The membership degree is obtained by the optimization of a defined objective function that measures the degree to which an alternative is similar/dissimilar to the Ideal/Anti-Ideal solutions. The closeness coefficient is used to rank the alternatives. To better have a high contrast between the ranks of alternatives an optimization problem was introduced and solved to maximize the contrast. The presented hybrid model was applied on an industrial case study for the selection of cans supplier/suppliers at Nutridar Factory in Amman-Jordan to demonstrate the proposed model. Finally a sensitivity analysis is introduced to verify the resulting ranks of the available suppliers via testing different values of the used parameters. The sensitivity analysis has shown robust and valid results that are close to real preferences of the consulted experts. [Copyright &y& Elsevier]

Abstract: The generic term ‘non-traditional machining’ (NTM) refers to a variety of thermal, chemical, electrical and mechanical material removal processes which have been developed due to lack of efficiency of the traditional machining processes to generate complex and intricate shapes in materials with ‘high strength-to-weight’ ratio. For effective utilization of the capabilities of different NTM processes, utmost care is needed for the selection of the most suitable process for a given machining application. Due to the lack of experienced experts in the domain of NTM processes, there is a need for a simple scientific/mathematical tool for selecting the most suitable NTM process when a particular shape feature is to be generated on a given work material. This paper focuses on the development of a two-phase decision model in this aspect. In the first phase, the most efficient NTM processes are selected for a given shape feature and work material combination having the best combination of performance parameters with the help of input-minimized-based Charnes, Cooper and Rhodes (CCR) model of data envelopment analysis (DEA). In the second phase, those efficient NTM processes are ranked in descending order of priority using the weighted-overall efficiency ranking method of multi-attribute decision-making (MADM) theory. Two real time machining applications are cited which prove the applicability, versatility and adaptability of this two-phase NTM process selection decision-making model as the results are quite consistent with those as derived by the past researches. [Copyright &y& Elsevier]

Abstract: Environmental impact assessment (EIA) is the assessment of the possible impact that a proposed plan or project may have on the environment, together consisting of the natural, social and economic aspects. The aim of this paper is to propose an environmental impact assessment methodology based on an integrated fuzzy AHP–ELECTRE approach in the context of urban industrial planning. In the proposed methodology the criteria weights are generated by a fuzzy AHP procedure. The fuzzy set theory is a perfect means for modeling uncertainty or imprecision arising from human mental phenomena. The usage of fuzzy sets in describing uncertainties and vagueness in different environmental factors simplifies the complex structure of EIA. A fuzzy outranking methodology, fuzzy ELECTRE is used to assess the environmental impact generated by the six different industrial districts which were predicted to shape the future industrial structure of Istanbul metropolitan area. Finally, a fuzzy dominance relation (FDR) methodology is used to rank the alternatives from the most risky to the least. A sensitivity analysis is also provided. [Copyright &y& Elsevier]

Abstract: Existing methodologies of equity investment, such as fundamental analysis, technical analysis, and institutional investor analysis, explore important factors of stock price behaviors. However, the interdependent relationships of the key factors have not yet been fully studied. This paper provides the first analysis on the interactive relationships among the factors in incorporating the methods of Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP). The empirical results show that factors from the existing analytical methodologies have significant interactive and self-feedback dynamics. Among the key factors, profitability is the most important one affecting investment decision, followed by growth and trading volume. In addition, due to the complexity of the ANP, this study proposes a new methodology to simplify the process, and empirical evidences indicate that the approach is effective and efficient. [Copyright &y& Elsevier]

Abstract: This paper considers a special case for logistics activities in Turkey: a joint selection of customs broker agency and international road transportation firm. For this purpose a decision-making team has been constituted, including members of logistics and finance departments and an academic. They determined related quantitative and qualitative criteria for the selection process. To cover the vagueness of related qualitative data, a fuzzy analytic network process (FANP) based model was formulated and applied to the decision-making process. The FANP model encompasses and substantially resolves the ambiguity and imprecision of the pairwise comparison process. By using the proposed FANP structure, the joint selection problem could be solved in a much easier way by also considering the inter-dependencies related to criteria. [Copyright &y& Elsevier]

Abstract: Forestation and forest preservation in urban watersheds are issues of vital importance as forested watersheds not only preserve the water supplies of a city but also contribute to soil erosion prevention. The use of fuzzy multiple criteria decision aid (MCDA) in urban forestation has the advantage of rendering subjective and implicit decision making more objective and transparent. An additional merit of fuzzy MCDA is its ability to accommodate quantitative and qualitative data. In this paper an integrated VIKOR–AHP methodology is proposed to make a selection among the alternative forestation areas in Istanbul. In the proposed methodology, the weights of the selection criteria are determined by fuzzy pairwise comparison matrices of AHP. It is found that Ömerli watershed is the most appropriate forestation district in Istanbul. [Copyright &y& Elsevier]

Abstract: In this paper, ELECTRE-TRI method has been used for ranking the optimal solutions of Non-dominated Sorting Genetic Algorithm-II (NSGA-II) which has been developed for multi-objective operation optimization of a cascade system of reservoirs. In the multi-objective optimization model, flood control and water supply have been considered as short-term and long-term objectives, respectively. The flood control objective function has been formulated to minimize the expected flood damages in different flooding months. A short-term reservoir optimization model which provides the optimal hourly releases during floods has been developed and linked to a flood damage estimation model. The water supply objective function minimizes water deficit damages in agricultural areas. The losses associated with deficit in supplying agricultural water demands have been calculated based on crop yield responses to deficit irrigation. Selection of the most practical solution among the optimal Pareto set of solutions, which is addressed using ELECTRE-TRI method, is a challenging issue. The proposed methodology provides an opportunity for further incorporation of decision makers’ preferences in ranking the NSGA-II optimal set of solutions. The results of applying the developed models to the cascade system of the Dez and Bakhtiari Reservoirs in southwest of Iran show that ELECTRE-TRI method has the ability to rank the non-dominated solutions of the multi-objective operation optimization model and provides a suitable framework for considering the preferences of decision makers (DMs). [Copyright &y& Elsevier]

Abstract: Energy planning is a complex issue which takes technical, economic, environmental and social attributes into account. Selection of the best energy technology requires the consideration of conflicting quantitative and qualitative evaluation criteria. When decision-makers’ judgments are under uncertainty, it is relatively difficult for them to provide exact numerical values. The fuzzy set theory is a strong tool which can deal with the uncertainty in case of subjective, incomplete, and vague information. It is easier for an energy planning expert to make an evaluation by using linguistic terms. In this paper, a modified fuzzy TOPSIS methodology is proposed for the selection of the best energy technology alternative. TOPSIS is a multicriteria decision making (MCDM) technique which determines the best alternative by calculating the distances from the positive and negative ideal solutions according to the evaluation scores of the experts. In the proposed methodology, the weights of the selection criteria are determined by fuzzy pairwise comparison matrices. The methodology is applied to an energy planning decision-making problem. [Copyright &y& Elsevier]

Abstract: The primary difficulty of support vector machine (SVM) model selection is heavy computational cost, thus it is difficult for current model selection methods to be applied in face recognition. Model selection via uniform design can effectively alleviate the computational cost, but its drawback is that it adopts a single objective criterion which can not always guarantee the generalization capacity. The sensitivity and specificity as multi-objective criteria have been proved of better performance and can provide a means for obtaining more realistic models. This paper first proposes a multi-objective uniform design (MOUD) search method as a SVM model selection tool, and then applies this optimized SVM classifier to face recognition. Because of replacing single objective criterion with multi-objective criteria and adopting uniform design to seek experimental points that uniformly scatter on whole experimental domain, MOUD can reduce the computational cost and improve the classification ability simultaneously. The experiments are executed on UCI benchmark, and on Yale and CAS-PEAL-R1 face databases. The experimental results show that the proposed method outperforms other model search methods significantly, especially for face recognition. [Copyright &y& Elsevier]

Abstract: This paper presents the Group Analytic Hierarchy Process Ordering (GAHPO) method: a new multi-criteria decision aid (MCDA) method for ordering alternatives in a group decision. The backbone of the method is the Analytic Hierarchy Process (AHP) which is separated into two hierarchies for a cost and a benefit analysis. From these two analyses, a partial ordinal ranking can be deduced, where three relations between alternatives exist: the preference, indifference, and incomparability. A complete cardinal ranking can also be deduced by dividing the score of the benefit analysis by the score of the cost analysis. Another particularity of GAHPO is the incorporation of ‘fairness’ when assigning weights to the decision makers. GAHPO has been developed to solve a real case: a selection of new production facilities with multiple stakeholders. By applying this method, we found four main advantages: significant reduction of time and effort in the decision process; easiness for the decision makers to arrive at a consensus; enhancement of the decision quality and documentation with justification of the decision made. In using the proposed method both efficiency and equity are achieved in the decision making process. [Copyright &y& Elsevier]

Abstract: Since 2000, the Industrial Development Bureau (IDB) of the Government in Taiwan has been implementing a policy of Electronic Manufacturing Promotion (e-MP) to assist firms to implement Business to Business Information System (B2BIS). In general, the actual performance of e-MP policy has just been based on the data given in a final report produced by the funded firm. Consequently there is no clear evidence as to the efficacy of the e-MP policy. Therefore, this paper mainly covers two parts (i) A Fuzzy analytic hierarchical process (Fuzzy AHP) was utilized to explore the weights of each policy item according to project leaders’ response of 17 funded cases to see whether the current e-MP policy really benefits firms and (ii) financial data of 30 cases was collected from the stock exchange in Taiwan to understand the actual performance and Fuzzy AHP was utilized to find the funded cases’ initial expectation to see whether the adoption of B2BIS by those cases funded by the Government actually met initial expectation. The results of this study indicate that the e-MP policy need to be adjust and costs decreased and work efficiencies rose are most important benefit in most of the funded cases after introduction of B2BIS and this meet their initial expectation. Finally, implications and suggestions are given for the e-MP policy to facilitate adjustments by the IDB. [Copyright &y& Elsevier]

Abstract: Collaborative R&D projects that are applied by innovative research teams (CIRT projects) are supported by government funding agencies in a number of countries due to the complexity and multidiscipline research of innovation. Government funding agencies invest heavily to CIRT projects every year. Thus, it is important to select the desired CIRT projects to avoid undesirable budget consumed. The purpose of this paper is to propose an integrated method for CIRT project selection. In this method, competitiveness and collaboration of candidate innovative research teams (IRTs) are used to assess and select projects. The criteria for competitiveness and collaboration are finalized in light of literature review as well as real situations. A formal decision procedure that aggregates competitiveness and collaboration performances of CIRTs is then presented. It integrates analytic hierarchy process (AHP), scoring method and weighted geometric averaging method. Some sample data from the National Natural Science Foundation of China (NSFC) is used to illustrate the potential application of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: Project complexity is ever growing and needs to be understood, analysed and measured better to assist modern project management. The overall ambition of this paper is therefore to define a measure of project complexity in order to assist decision-making, notably when analysing several projects in a portfolio, or when studying different areas of a project. A synthesised literature review on existing complexity measures is firstly proposed in order to highlight their limitations. Then, we identify the multiple aspects of project complexity thanks to the construction and refinement of a project complexity framework thanks to an international Delphi study. We then propose a multi-criteria approach to project complexity evaluation, underlining the benefits of such an approach. In order to solve properly this multi-criteria problem, we first conduct a critical state of the art on multi-criteria methodologies. We then argue for the use of the Analytic Hierarchy Process. In the end, this tool permits to define a relative project complexity measure, which can notably assist decision-making. Complexity scales and subscales are defined in order to highlight the most complex alternatives and their principal sources of complexity within the set of criteria and sub-criteria which exist in the hierarchical structure. Finally, a case study within a start-up firm in the entertainment industry (musicals production) is performed. Conclusions, limitations and perspectives of research are given in the end. [ABSTRACT FROM AUTHOR]

Abstract: Partner selection is an important issue in the supply chain management. Since environment protection has been of concern to public in recent years, and the traditional supplier selection did not consider about this factor; therefore, this paper introduced green criteria into the framework of supplier selection criteria. The aim of this research was to develop an optimum mathematical planning model for green partner selection, which involved four objectives such as cost, time, product quality and green appraisal score. In order to solve these conflicting objectives, we adopted two multi-objective genetic algorithms to find the set of Pareto-optimal solutions, which utilized the weighted sum approach that can generate more number of solutions. In experimental analysis, we introduced a {4,4,4,4} supply chain network structure, and compared average number Pareto-optimal solutions and CPU times of two algorithms. [ABSTRACT FROM AUTHOR]

Abstract: Multiple criteria ABC inventory classification is one of the most common techniques of planning and controlling of inventory. In this type of classification, other criteria in addition to the criterion of annual dollar usage are taken into account, and then items, based on their priority, are divided into 3 classes with different ordering policies (OPs). In this paper, multiple criteria ABC inventory classification is first performed using the . Then suitable OPs are determined for items of classes A and C and Finally, we apply the approach to extract fuzzy rules from the policies of these two classes for determining the policies of items class B. To show applicability of the proposed model, it is then implemented in a soft-drink manufacturing factory. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we present a new approach for fuzzy multiple attributes group decision-making based on fuzzy preference relations. First, we construct fuzzy importance matrices for decision-makers with respect to attributes and construct fuzzy evaluating matrices for decision-makers with respect to the attributes of the alternatives. Based on the fuzzy importance matrices and the fuzzy evaluating matrices, we construct fuzzy rating vectors for decision-makers with respect to the alternatives. Then, we defuzzify the trapezoidal fuzzy numbers in the constructed fuzzy rating vectors to get the rating vectors for the decision-makers. Based on the rating vectors, we construct fuzzy preference relations for the decision-makers with respect to the alternatives. Based on the fuzzy preference relations, we calculate the average rating value of each decision-maker with respect to the alternatives. Then, we sort these average rating values in a descending sequence and assign them different scores. Then, we calculate the summation values of the scores of the alternatives with respect to each decision-maker, respectively. The larger the summation values of the scores, the better the choice of the alternative. The proposed method is simpler than for handling fuzzy multiple attributes group decision-making problems. It provides us with a useful way to handle fuzzy multiple attributes group decision-making problems. [ABSTRACT FROM AUTHOR]

Abstract: E-alliance is the union of e-commerce and its success and efficiency is related to comprehensive quality of e-commerce. Thus, ranking e-commerce websites in e-alliance is of importance, which is a multi-criteria decision-making (MCDM) problem. This paper proposes an evaluation model based on analytic hierarchy process (AHP), fuzzy sets and technique for order performance by similarity to ideal solution (TOPSIS), to tackle the issue in fuzzy environment. The AHP is applied to analyze the structure of ranking problem and to determine weights of the criteria, fuzzy sets is utilized to present ambiguity and subjectivity with linguistic values parameterized by triangular fuzzy numbers, and TOPSIS method is used to obtain final ranking. Case analysis is conducted to illustrate the utilization of the model for the problem. It demonstrates the effectiveness and feasibility of the proposed model. [ABSTRACT FROM AUTHOR]

Abstract: In order to efficiently control the inventory items and determine the suitable ordering policies for them, multi-criteria ABC inventory classification, which is one of the most common techniques of production and inventory control, is used. In this classification, other criteria in addition to annual dollar usage are taken into account and then the items are classified in three classes with different ordering policies, based on their priority. In this paper, we propose an integrated fuzzy analytic hierarchy process-data envelopment analysis (FAHP-DEA) for multiple criteria ABC inventory classification. The proposed FAHP–DEA methodology uses the FAHP to determine the weights of criteria, linguistic terms such as Very High, High, Medium, Low and Very Low to assess each item under each criterion, the data envelopment analysis (DEA) method to determine the values of the linguistic terms, and the simple additive weighting (SAW) method to aggregate item scores under different criteria into an overall score for each item. The integrated FAHP–DEA methodology is illustrated using a real case study. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we investigate hybrid multiple attribute decision making problems with various forms of attribute values (real numbers, linguistic labels, interval numbers, intuitionistic fuzzy numbers and interval intuitionistic fuzzy numbers). We propose a method based on preference degrees which may take the forms of fuzzy numbers, intuitionistic fuzzy numbers and interval intuitionistic fuzzy numbers. The method first normalizes various forms of attribute values into preference degrees, and then uses a preference degree-based weighted averaging operator to aggregate the normalized preference degrees. Meanwhile, for convenience of calculation, a new linguistic representation model is presented, whose feasibility is verified by comparing it with the traditional 4-tuple linguistic representation model, and from our model, the mapping relationship between interval intuitionistic fuzzy numbers and linguistic labels can be constructed. Finally, we illustrate the rationality and practicality of the proposed method by an application example. [ABSTRACT FROM AUTHOR]

Abstract: In the present day business environment, customer satisfaction is a pre-requisite for providing good service to the customer. The present day market is a customer driven market and only those who can fulfill customer demands at minimal rate and in shortest time can share a greater market share. Owing to the aforementioned factors, the problem of customers’ allocation to the vendors is considered to be very important problem and has attracted the attention of a lot of researchers. In this paper, a multiple vendor transportation problem having a variety of products and multiple customers has been taken into consideration. The problem considers two criteria: transportation time and transportation cost, thus making it a multi-criteria problem. To solve this problem, a heuristic based on a new approach, called artificial immune system (AIS) has been proposed. To strengthen AIS, a fuzzy logic controller (FLC) has been incorporated in the AIS heuristic. FLC changes the hyper mutation rate adaptively at iteration. A benchmark problem from the prominent literature review has been taken for showing the efficacy of the proposed algorithm. The supremacy of the problem has been shown by the randomly generated data set with increased complicacy of the problems. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, an interactive approach based method is proposed for solving multi-objective optimization problems. The proposed method can be used to obtain those Pareto-optimal solutions of the mathematical models of linear as well as nonlinear multi-objective optimization problems modeled in fuzzy or crisp environment which reasonably meet users aspirations. In the proposed method the objectives are treated as fuzzy goals and the satisfaction of constraints is considered at different α-level sets of the fuzzy parameter used. Product operator is used to aggregate the membership functions of the objectives. To initiate the algorithm, the decision maker has to specify his(er) preferences for the desired values of the objectives in the form of reference levels in the membership space. In each iterative phase, a single objective nonlinear (usually nonconvex) optimization problem has to be solved. It is solved using real coded genetic algorithm, MI-LXPM. Based on its outcomes, the decision maker has the option to modify, if felt necessary, some or all of the reference levels in the membership function space before initiating the next iterative phase. The algorithm is stopped where user’s aspirations are reasonably met. [ABSTRACT FROM AUTHOR]