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Abstract: Out of several generalizations of fuzzy set theory for various objectives, the notions introduced by in defining intuitionistic fuzzy sets and interval-valued intuitionistic fuzzy sets are interesting and very useful in modeling real life problems. Ranking of interval-valued intuitionistic fuzzy sets plays a vital role in decision-making, data analysis, artificial intelligence and socioeconomic system and it was studied in . In this paper a new method for ranking interval-valued intuitionistic fuzzy sets has been introduced and studied. The method is illustrated by numerical examples and compared with other methods. And then a new method for handling multi-criteria fuzzy decision-making problems based on interval-valued intuitionistic fuzzy sets is presented in which criterion values for alternatives are interval-valued intuitionistic fuzzy sets. The method proposed here can provide a useful way to efficiently help the decision-maker to make his decision. An illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

Abstract: Traditionally, most importance-assessing methods used to demonstrate the importance among criteria by preference weightings are based on the assumptions of additivity and independence. In fact, people have found that using such an additive model is not always feasible because of the dependence and feedback among the criteria to somewhat different degrees. To solve the issue the analytic network process (ANP) method is proposed by Saaty. The general method is easy and useful for solving the above-mentioned problem. However in ANP procedures, using average method (equal cluster-weighted) to obtain the weighted supermatrix seems to be irrational because there are different degrees of influence among the criteria. Therefore, we intended to propose an integrated multiple criteria decision making (MCDM) techniques which combined with the decision making trial and evaluation laboratory (DEMATEL) and a novel cluster-weighted with ANP method in this paper, in which the DEMATEL method is used to visualize the structure of complicated causal relationships between criteria of a system and obtain the influence level of these criteria. And, then adopt these influence level values as the base of normalization supermatrix for calculating ANP weights to obtain the relative importance. Additionally, an empirical study is illustrated to demonstrate that the proposed method is more suitable and reasonable. By the concept of ideal point, some important conclusions drawn from a practical application can be referred by practitioners. [ABSTRACT FROM AUTHOR]

Abstract: A multi-attribute group decision-making method based on weighted aggregation operators is presented to solve the decision-making problems which the attribute values and the weights take the form of interval-valued trapezoidal fuzzy numbers (GIVTFN). First, some properties are defined, such as the concept and the relational calculation rules of GIVTFN, the distance and its characteristics of GIVTFN, and the method of linguistic terms transformed into GIVTFN. Second, the normalization method of GIVTFN, generalized interval-valued trapezoidal fuzzy number weighted aggregation operator (ITWA), the generalized interval-valued trapezoidal fuzzy number ordered weighted aggregation operator (ITOWA), and the generalized interval-valued trapezoidal fuzzy numbers hybrid aggregation operator (ITHA) are proposed. The group decision methods based on these operators are also illustrated. Finally, in this paper an illustrative example is given to show this decision-making steps and the effectiveness of this method. [Copyright &y& Elsevier]

Abstract: The Limitations and deficiencies of existing score functions of intuitionistic fuzzy set are analyzed. Based on the two theories of intuitionistic fuzzy set and cross entropy, with the adoption of cross entropy of the degree of membership from the degree of non-membership handling the effect of hesitancy degree, two improved methods handling multicriteria fuzzy decision-making problem are provided. They are called score function method and weighted score function method. Finally, examples are given showing that the methods presented in this paper are more efficient and advantageous. [Copyright &y& Elsevier]

Abstract: This paper proposes the concept of intuitionistic fuzzy weighted entropy, and presents a new method for intuitionistic fuzzy multicriteria decision making problems. We first introduce some classical intuitionistic fuzzy entropy measures and verify the entropy of the intuitionistic fuzzy set is the average value of the entropies of its intuitionistic fuzzy values. Then, we present the concept of the intuitionistic fuzzy weighted entropy, which is a natural extension of the entropy for intuitionistic fuzzy sets. Some important weight entropy measures, such as the weighted Szmidt and Kacprzyk entropy, the weighted De Luca–Termini entropy, the weighted score function based entropy, and the weighted min–max entropy, are also given. According to the minimum entropy principle, we establish the programming model to generate optimal weight of criteria, and present the corresponding multicriteria decision making method. Finally, two illustrative examples are given to verify the developed approach. [Copyright &y& Elsevier]

Abstract: In this paper, we have developed a modular Decision Support System (DSS) in order to select an optimum portfolio of several chances for investments in presence of uncertainty. The investments are considered as the projects so as their initial investment costs, profits, resource requirement, and total available budget are assumed to be uncertain. This uncertainty has been modeled using fuzzy concepts. The proposed DSS has two main modules. The first one is a fuzzy binary programming model which represents the mathematical model of the associated fuzzy capital-budgeting problem. It involves finding optimum combination of investment portfolio considering a multi-objective measurement function and subject to several set of constraints. The results of optimistic and pessimistic analysis of the aforementioned fuzzy binary programming model plus a managerial Confidence Level (CL) value are treated as input of a fuzzy rule based system which is the second module of the proposed DSS. Although some projects are simple to make a decision about at the final step of the first module but the unique output of the second module of the proposed DSS is Risk of Investment (ROI) for all remained project. The logic relations between precedence parts of the rules as well as CL value will work in favor of computational efforts in second module through diminishing some unessential rules. This will help to define a complete set of fuzzy IF-THEN rules more efficiently. The proposed DSS can help the decision makers to select an optimum investment portfolio with minimum risk in a complete ambiguous condition. [Copyright &y& Elsevier]

Abstract: This paper deals with multi-criteria decision making (MCDM) problems with multiple priorities, in which priority weights associated with the lower priority criteria are related to the satisfactions of the higher priority criteria. Firstly, we propose a prioritized weighted aggregation operator based on ordered weighted averaging (OWA) operator and triangular norms (t-norms). To preserve the tradeoffs among the criteria in the same priority level, we suggest that the degree of satisfaction regarding each priority level is viewed as a pseudo criterion. On the other hand, t-norms are used to model the priority relationships between the criteria in different priority levels. In particular, we show that strict Archimedean t-norms perform better in inducing priority weights. As Hamacher family of t-norms provide a wide class of strict Archimedean t-norms ranging from the product to weakest t-norm, Hamacher parameterized t-norms are used to induce the priority weight for each priority level. Secondly, considering decision maker (DM)’s requirement toward higher priority levels, a benchmark based approach is proposed to induce priority weight for each priority level. In particular, Łukasiewicz implication is used to compute benchmark achievement for crisp requirements; target-oriented decision analysis is utilized to obtain the benchmark achievement for fuzzy requirements. Finally, some numerical examples are used to illustrate the proposed prioritized aggregation technique as well as to compare with previous research. [Copyright &y& Elsevier]

Abstract: Although all university majors are prominent, and the necessity of their presence is of no question, they might not have the same priority basis considering different resources and strategies that could be spotted for a country. Their priorities likely change as the time goes by; that is, different majors are desirable at different time. If the government is informed of which majors could tackle today existing problems of world and its country, it surely more esteems those majors. This paper considers the problem of clustering and ranking university majors in Iran. To do so, a model is presented to clarify the procedure. Eight different criteria are determined, and 177 existing university majors are compared on these criteria. First, by k-means algorithm, university majors are clustered based on similarities and differences. Then, by AHP algorithm, we rank university majors. [Copyright &y& Elsevier]

Abstract: The use of elements of artificial intelligence, including knowledge-based systems, becomes more and more widespread in aiding design problem solutions. The authors have been working on problems of control systems for many years. A design process involves many decision problems connected with, for example, a choice of a subsystem structure, subunits or particular elements selection. Because of such regards, it was decided to extend knowledge-based system with a module for support of such decision making. In this paper, an elaborated module for decision-making support is considered. The basic theoretical assumptions concerning the accepted method of multiattribute decision making based on pairwise comparison in categories of hierarchical decision process (AHP) is presented. Accepted knowledge representation in AHP method and pairwise comparison method and methods of expert knowledge acquisition are discussed. The module functioning is illustrated by an example of choice of temperature sensors in a system of fuel transport to Diesel engine of a main propulsion unit of a ship. [Copyright &y& Elsevier]

Abstract: Supplier selection is a multi criteria decision-making problem that comprises tangible and intangible factors. The majority of previous supplier selection techniques do not consider strategic perspective. Besides, uncertainty is one of the most important obstacles in supplier selection. In this paper, quantified SWOT is applied in the context of supplier selection for the first time. SWOT (Strengths, Weaknesses, Opportunities and Threats) is one of the most well-known techniques for conducting a strategic study. In addition, the fuzzy logic and triangular fuzzy numbers are integrated with SWOT analysis – as a novel innovation – to deal with vagueness of human thought. SWOT analysis can consider both qualitative and quantitative criteria. The managers can understand the position of suppliers in a competitive environment with a glance at SWOT matrix. Moreover, a fuzzy linear programming model is proposed to determine how much should be purchased from each supplier. It is supposed that the demand is a fuzzy number. Besides, the capacity of warehouse is considered as a constraint. A case study is utilized concurrently to show the efficiency of the proposed model. [Copyright &y& Elsevier]

Abstract: This research proposes a novel MCDM model, including DEMATEL, ANP, and VIKOR for exploring portfolio selection based on CAPM. We probe into the influential factors and relative weights of risk-free rate, expected market return, and beta of the security. The purpose of this research is to establish an investment decision model and provides investors with a reference of portfolio selection most suitable for investing effects to achieve the greatest returns. Taking full consideration of the interrelation effects among criteria/variables of the decision model, this paper examined leading semiconductor companies spanning the hottest sectors of integrated circuit (IC) design, wafer foundry, and IC packaging by experts. Empirical findings revealed that risk-free rate was affected by budget deficit, discount rate, and exchange rate; expected market return was affected by country risk, industrial structure, and macroeconomic factors; and beta of the security was affected by firm-specific risk and financial risk. Also, the factors of the CAPM possessed a self-effect relationship according to the DEMATEL technique. In the eight evaluation criteria, macroeconomic criterion was the most important factor affecting investment decisions, followed by exchange rate and firm-specific risk. In portfolio selection, leading companies in the wafer foundry industry outperformed those in IC design and IC packaging, becoming the optimal portfolio of investors during the time that this study was conducted. [Copyright &y& Elsevier]

Abstract: Taking account of uncertainty in multicriteria decision making problems is crucial due to the fact that depending on how it is done, ranking of alternatives can be completely different. This paper utilizes linguistic values to evaluate the performance of qualitative criteria and proposes using appropriate shapes of fuzzy numbers to evaluate the performance of quantitative criteria for each problem with respect to its particular conditions. In addition, a process to determine the weights of criteria using fuzzy numbers, which considers their competition to gain greater weights and their influence on each other is described. A new fuzzy methodology is proposed to solve such a problem that utilizes parametric form of fuzzy numbers. The case study of diversion of water into Lake Urmia watershed, which is defined using triangular, trapezoidal, and bell-shape fuzzy numbers demonstrates the utility of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: This paper models the aeroengine health assessment problem as a multi-criteria decision-making (MCDM) problem and proposes a three-step evaluation model, which combines the techniques of fuzzy analytic hierarchy process (fuzzy AHP), fuzzy preference programming (FPP) and technique for order performance by similarity to ideal solution (TOPSIS). Fuzzy AHP and FPP methods are used to determine the relative weights of multiple evaluation criteria and synthesize the ratings of candidate aeroengines. Aggregated the evaluators’ attitude toward preference, then TOPSIS is employed to obtain a crisp overall performance value for each alternative to make a final decision. To illustrate how the approach is used for the aeroengine health assessment problem, an empirical study of a real case involving eleven evaluation criteria and ten initial commercial aeroengines of Air China Ltd. is conducted. The case study demonstrates the effectiveness and feasibility of the proposed evaluation procedure. [ABSTRACT FROM AUTHOR]

Abstract: The intuitionistic fuzzy (IF) set characterized by two functions was a generalization of the fuzzy set. In this paper, we investigate multiattribute decision making (MADM) problems with ratings of alternatives being expressed using IF sets and attribute weights given as real numbers. Firstly, the generalized ordered weighted averaging (GOWA) operators introduced by Yager [Yager, R. (2004). Generalized OWA aggregation operators. Fuzzy Optimization and Decision Making, 3, 93–107] are extended to aggregate IF sets. Secondly, MADM problems with IF sets are formulated through transforming the ratings of alternatives on both qualitative and quantitative attributes into IF sets in a unified way. The method and procedure based on the extended GOWA operators are developed to solve the MADM problems with IF sets. Finally, the effectiveness and practicability of the proposed method are illustrated with a numerical example. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a new multi-perspective framework for multi-attribute decision making, and illustrates its mathematical descriptions and procedure. The main steps of the procedure are: construct the attribute set; construct the evaluation object set; construct evaluation perspectives with corresponding attributes and weights; select evaluation algorithms for different perspectives; and carry out cluster analysis on the multidimensional evaluation results. This framework can effectively solve the problem of attribute overlapping of different perspectives and proper algorithms can be applied to different perspectives according to their characteristics. Based on the business data of a tobacco company, a customer evaluation system is designed according to this framework. Results show that the framework is effective and practical. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we propose an integrated model from the most important and usable Multi-Criteria Decision Making (MCDM) techniques, means Analytic Hierarchy Process (AHP) and Technique for Ordering Preference by Similarity to Ideal Solution (TOPSIS), in order to examine the improvement fields of Iran automobile industry. A new approach, AT method, has been suggested to combine the results of two techniques to find the final ranking. Besides, we propose a developing Data Envelopment Analysis (DEA) model as a basis for comparing the reliability of results of the MCDM techniques, which depicts AT is more reliable than AHP and TOPSIS. Our results have certified that safety and then price are the customers’ most important criteria for automobile selection. After comparing the internal and external products, and ranking them based on the criteria and sub-criteria, the necessity to improve internal automobiles on various fields has been prioritized. [ABSTRACT FROM AUTHOR]

Abstract: It is crucial to obtain automatically and efficiently a well-distributed set of Pareto optimal solutions in multiobjective evolutionary algorithms (MOEAs). Many studies have proposed different evolutionary algorithms that can progress toward the Pareto front with a widely spread distribution of solutions. However, most theoretically, convergent MOEAs necessitate certain prior knowledge about the Pareto front in order to efficiently maintain widespread solutions. In this paper, we propose, based on the new E-dominance concept, an Adaptive Rectangle Archiving (ARA) strategy that overcomes this important problem. The MOEA with this archiving technique provably converges to well-distributed Pareto optimal solutions without prior knowledge about the Pareto front. ARA complements the existing archiving techniques and is useful to both researchers and practitioners. [ABSTRACT FROM AUTHOR]

Abstract: Due to the occurrence of several recent threats, such as, from an international perspective, SARS, the 9/11 terrorist attack, increases in the price of oil, depressions in the economy, and, from a domestic perspective, increasing interaction with China, joining the WTO, low railway prices, and high-speed rail development, resulting in passenger rate dropping drastically, an increasing number of Taiwanese airlines have been facing deficits or closing down in recent years. Therefore, long-term strategies for gaining a competitive advantage are now starting to focus on innovation rather than cost reduction. Although attention to the importance of innovation is rising, there are few studies today that provide airlines with a clear and precise way to successfully conduct innovation operations. The aim of this study is to solve this dilemma by constructing a novel aviatic innovation system (AIS). In this paper, a hybrid fuzzy multiple criteria decision-making (MCDM) model based on a fuzzy analytical hierarchical process (FAHP) and a VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is adopted to complete the construction of the AIS. The value of the AIS is to provide Taiwanese airlines with innovation-oriented techniques for future strategy development. We believe that the AIS can contribute to the survival of Taiwanese airlines in the near future. [ABSTRACT FROM AUTHOR]

Abstract: Recommendation systems that provide appropriate solutions to users to reduce their decision complexity have become popular in the Internet world. Designing and evaluating such systems remain essential challenges to researchers and practitioners. Toward that end, a critical task is how to obtain user preferences. Mobile phones have become indispensable in everyday life, yet fierce market competition, characterized by rapid introductions of different models with novel designs and advanced features, have made consumers’ purchase decision making increasingly complex. As a well-established, multiple criteria decision technique, analytic hierarchy processing (AHP) provides an intuitive model of a hierarchical structure capable of supporting complex product comparisons and evaluations by consumers. In this paper, we illustrate the application of an AHP-based mechanism to develop a Web-based recommendation system and empirically evaluate the prototype by conducting a controlled experiment with 244 mobile phone users, focusing on both content and system satisfaction. Our evaluation includes benchmark systems built on rank-based analysis and an equal weight-based system as comparative baselines. Overall, the results suggest the viability and value of using AHP to construct effective recommendation systems. Subjects appear satisfied with the recommendations by the AHP-based system, though its relatively demanding input requirements may need mitigation and adequate interface designs. This study contributes to research and practice in recommender systems in general and helps develop mobile phone recommendation systems for online stores and consumers in particular. [ABSTRACT FROM AUTHOR]

Abstract: It is known that a hierarchical decision structure consisting of multiple criteria can be modeled by a Choquet integral-based hierarchical network. With a given input–output dataset, the degree of importance of each criterion can be directly obtained from the corresponding connection weight after the network has been trained from samples. Since each output value or the synthetic evaluation of an alternative derived from uncertain assessments has its upper and lower bounds, the degree of importance of each criterion should not be unique and can be distributed in a range. In this paper, the range of the degree of importance of each criterion is obtained by three Choquet integral-based hierarchical networks with the pre-specified hierarchical structure: one is a common network constructed by merely minimizing the least squared error, and the others are employed to determine a nonlinear interval regression model. The above three networks are trained with a given input–output dataset using the proposed genetic algorithm-based learning algorithm. Empirical results of evaluating customer service perceptions on fast food stores demonstrate that the proposed method can identify key factors that have stronger effect on service quality perceptions by employing three Choquet integral-based hierarchical networks with the hierarchical structure to determine possible ranges of the degree of importance of respective aspects and attributes. [ABSTRACT FROM AUTHOR]

Abstract: The concept of Atanassov’s intuitionistic fuzzy sets is a generalization of ordinary fuzzy sets. Under the intuitionistic fuzzy decision environment, this paper develops optimistic and pessimistic point operators to draw the influences of optimism and pessimism on multiple criteria decision analysis. We propose the optimistic and pessimistic score functions based on point operators to measure evaluations of the alternative with respect to each criterion. The suitability function can then be established to determine the degree to which the alternative satisfies the decision maker’s requirement. An optimization model with suitability functions is propounded on account of ill-known membership grades to generate optimal weights for criteria. Finally, an outcome-oriented approach is adopted to validate the proposed methods. Several multiattribute evaluation cases in consumer decision making reality are addressed to examine the feasibility and applicability of the current method. From the empirical results of effectiveness examination, the proposed intuitionistic fuzzy multicriteria decision making method with optimistic/pessimistic score functions performed significantly better than the method without consideration of optimism/pessimism. Therefore, we can conclude that the proposed methods by using intuitionistic fuzzy optimistic/pessimistic point operators have desirable potentials in practice. [ABSTRACT FROM AUTHOR]

Abstract: As the advanced integration of communications, information and vehicle technologies, Vehicle Telematics Systems (VTS), have been initiated for satisfying consumers’ needs with respect to automobile movement. Importantly, VTS enables a vehicle to become a multifunction mobile-services platform. Cars are now designed not only for transportation, but also to provide value-added services covering navigation, safety, security, information, communications and entertainment. Drivers or passengers can contact a call center via VTS to access aspired/desired services and information online. Therefore, VTS increases both the utility/functions and the safety of driving. Developing the optimal VTS that satisfies with consumers’ needs has become the foremost concern of automobile producers. This study will attempt to identify the required VTS utilities between distinguishing characteristics/features of consumers and propose the ideal service combinations for the next e-era generation VTS. An evaluating model by six aspects to be considered/constructed, which encompasses 25 criteria, is built to identify consumers’ needs for the next e-era generation VTS. In the paper, a Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique is used to construct the network relation-map (NRM) among the criteria of each aspect. These criteria are not mutually independent; instead, they have feedback mechanisms. The Analytical Network Process (ANP) based on NRM is used to determine the relative weightings among those criteria. Moreover, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is used to determine and improve the gaps among the distinguishing characteristics/features of consumers’ desired utilities with respect to services/provide the decision-maker of Telemetics Service Provider (TSP) for improving existing functions or planning further utilities in the next-generation VTS. Based on above NRM those results can be served as a suggestion for the TSP to improve the existing functions or plan further utilities/functions for reducing the gaps and satisfying the users’ needs in next e-era generation VTS. [Copyright &y& Elsevier]

Abstract: Design concept evaluation which is in the end of conceptual design is one of the most critical decision points in product development. It relates to the final success of product development, because a poor design concept can rarely be compensated at the later stages. Design concept evaluation is a complicated multi-criteria decision-making problem under uncertain environments. Vague set theory is superior to fuzzy set theory in dealing with uncertain and imprecise judgments of decision makers (DMs) due to its ability of supporting opposing evidences. In this paper, a new integrated design concept evaluation approach based on vague sets is presented. Linguistic variables are transformed into vague numbers by vague set theory. Modified weighted least squares model (WSLM) based on vague sets is proposed to aggregate all individual judgments in group decision-making. Vague cross-entropy integrated with the technique for order preference by similarity to ideal solution (TOPSIS) framework is proposed to rank the order of alternatives according to the synthetic vague decision matrix. Numerical example of design concept evaluation problem of a horizontal directional drilling (HDD) machine indicates that the proposed integrated approach is systematic and effective to solve design concept evaluation problem regardless of complexity of product. [Copyright &y& Elsevier]

Abstract: Since the correct energy policy affects economic development and environment, the most appropriate energy policy selection is excessively important. Recently some studies have concentrated on selecting the best energy policy and determining the best energy alternatives. In most of these studies, multicriteria and fuzzy approaches to energy policy making are frequently used. The fuzzy set theory is a powerful tool to treat the uncertainty in case of incomplete or vague information. In this paper, a fuzzy multicriteria decision-making methodology is suggested for the selection among energy policies. The methodology is based on the analytic hierarchy process (AHP) under fuzziness. It allows the evaluation scores from experts to be linguistic expressions, crisp or fuzzy numbers. In the application of the proposed methodology, the best energy policy is determined for Turkey. [Copyright &y& Elsevier]

Abstract: The key issue for decision making in stock trading is selection of the right stock at the right time. In order to select the superior stocks (alternatives) for investment, a finite number of alternatives have to be ranked considering several and sometimes conflicting criteria that often are vague and have uncertainty conditions. Therefore, we are faced with a special Multiple Criteria Decision Making (MCDM) problem. The purpose of this paper is to develop a fuzzy expert system for selecting superior stocks in order to encounter the uncertainty of stock portfolio recommendation and model the recommendation rules which experts at Tehran Stock Exchange (TSE) use for portfolio recommendation. The results of implementing the designed fuzzy expert system at TSE were affirmative. [Copyright &y& Elsevier]

Abstract: In this paper, we focus on multiobjective integer programming problems involving random variable coefficients in objective functions and constraints. Using the concept of chance constrained conditions, such multiobjective stochastic integer programming problems are transformed into deterministic ones based on the fractile criterion optimization model. As a fusion of stochastic programming and fuzzy one, we introduce fuzzy goals representing the ambiguity of the decision maker’s judgments into them and define M--efficiency, a new concept of efficient solution, as a fusion of stochastic approaches and fuzzy ones. Then, we construct an interactive fuzzy satisficing method using genetic algorithms to derive a satisficing solution for the decision maker which is guaranteed to be M--efficient by updating the reference membership levels. Finally, the efficiency of the proposed method is demonstrated through numerical experiments. [Copyright &y& Elsevier]

Abstract: Gas molecules within an enclosure will always tend to a homogenous and uniform equilibrium with maximum entropy, even without any prior knowledge on the geometry and state of the enclosure. Furthermore, if an uneven potential field was present, more molecules will tend to reside in the lower potential region as dictated by the Maxwell–Boltzmann distribution. The inherent diverse behavior of molecular system and their converging drift pressure in potential fields seems to be applicable for the contrary goals of proximity and diversity in multi-objective optimization. Inspired by this association, this paper will explore the notion of exploiting molecular motion to solve multi-objective problems. By adapting the algorithmic structure of molecular dynamics, which essentially represents a technique for the computer simulation of molecular motion, a molecular system that is relevant for multi-objective optimization is proposed, known as molecular dynamics optimizer (MDO). The performance of MDO was compared with other conventional multi-objective optimizers, specifically EA and PSO, in several multi-objective benchmark problems and the experimental results demonstrated that MDO is indeed a viable and practical approach for multi-objective optimization. [Copyright &y& Elsevier]

Abstract: This paper proposes an improved multi-objective particle swarm optimizer with proportional distribution and jump improved operation, named PDJI-MOPSO, for dealing with multi-objective problems. PDJI-MOPSO maintains diversity of new found non-dominated solutions via proportional distribution, and combines advantages of wide-ranged exploration and extensive exploitations of PSO in the external repository with the jump improved operation to enhance the solution searching abilities of particles. Introduction of cluster and disturbance allows the proposed method to sift through representative non-dominated solutions from the external repository and prevent solutions from falling into local optimum. Experiments were conducted on eight common multi-objective benchmark problems. The results showed that the proposed method operates better in five performance metrics when solving these benchmark problems compared to three other related works. [Copyright &y& Elsevier]

Abstract: Data Envelopment Analysis (DEA) is recognized as a modern approach to the assessment of performance of a set of homogeneous Decision Making Units (DMUs) that use similar sources to produce similar outputs. While DEA commonly is used with precise data, recently several approaches are introduced for evaluating DMUs with uncertain data. In the existing approaches many information on uncertainties are lost. For example in the defuzzification, the -level and fuzzy ranking approaches are not considered. In the tolerance approach the inequality or equality signs are fuzzified but the fuzzy coefficients (inputs and outputs) are not treated directly. The purpose of this paper is to develop a new model to evaluate DMUs under uncertainty using Fuzzy DEA and to include -level to the model under fuzzy environment. An example is given to illustrate this method in details. [Copyright &y& Elsevier]

Abstract: Selection of qualified human resources is a key success factor for an organization. The complexity and importance of the problem call for analytical methods rather than intuitive decisions. The aim of this paper is to support adequately the decision making process. The steps of fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) are considered, incorporating a new concept for the ranking of the alternatives. This is based on the veto threshold, a critical characteristic of the main outranking methods. The ultimate decision criterion is not the similarity to the ideal solution but the distance of the alternatives from the veto set by the decision makers. Additionally, a real life application on the selection of a top management team member shows the practical implications. [Copyright &y& Elsevier]

Abstract: Outsourcing manufacturing is a trend in today’s global business operations. Vendor selection is an essential factor affecting outsourcing operations performance and has been determined as a multiple criteria decision making (MCDM) problem. The purpose of this paper is to propose a novel hybrid MCDM technique to cope with the complex and interactive vendor evaluation and selection problem which can determine the structural relationships and the interrelationships amongst all the evaluation’s dimensions and support the Analytic Network Process (ANP) method to arrange appropriate weightings to each dimension and criterion in the evaluation model by summarizing the opinions of the experts. Finally, the overall performance ranking of all alternatives can be obtained to assist the decision making. Taiwan semiconductor industry is the largest provider in worldwide market. It is vertically disintegrated and outsourcing is a main stream practice. Wafer-testing is a critical manufacturing step in the semiconductor supply chain that distinguishes whether the IC can meet the specifications. Consequently, it’s crucial to establish a thorough model for selecting the wafer-testing vendors in order to achieve the success of the outsourcing operation. A case study of a Taiwan semiconductor company in selecting its wafer-testing outsourcing vendor by using the proposed MCDM technique is demonstrated to enhance the decision making quality. The results and proposed solution can be referred to by not only the semiconductor companies, but also other industries so that they can improve the vendor selection process in order to achieve a higher performance and satisfaction level. [Copyright &y& Elsevier]

Abstract: The most commonly used measures for evaluating the competing mutual funds are “Treynor Ratio”, “Sharpe Ratio” and “Jensen’s Alpha”. One also uses another measure called the “Information Ratio”. However, it is not clear which measure is the most robust. The purpose of our study is to evaluate the performance of mutual funds under the broad framework of multi-attribute decision analysis approach where each criterion can be taken into consideration in making a final ranking of the mutual funds. In this paper we adopt the concepts of “Ideal” and “Anti-Ideal” solutions as suggested by , and study the extended technique for order preference by similarity to the ideal solution (TOPSIS) method using two different “distance” ideas, namely – “Minkowski’s metric” and “Mahalanobis” distances. The broad framework with the two aforementioned distances is then applied to evaluate the performance of 82 Taiwanese mutual funds for consecutive 34 months. The empirical results show that using TOPSIS methods incorporated Minkowski’s distance measure to evaluate the mutual funds’ performance perform well. [Copyright &y& Elsevier]

Abstract: Intellectual property (IP) management has been widely accepted as an important topic to support the technological innovation. In order to effectively and efficiently implement IP management, it is more practical to firstly focus on the most important aspects which, in turn, provide immediate beneficial results to allow organizations to further implementing other aspects by allocating more resources. The authors propose an IP management excellence audit system that breaks down the complicated IP management practices into a list of enabling criteria and the IP management performance in various criteria can be measured in details. The enabling criteria are the critical success factors to good IP management system and practice. Analytic hierarchy process approach is used to determine the relative importance among the identified criteria in the IP management excellence audit system. The evidential reasoning approach is adopted to develop an expert assessment tool to carry out the audit of organizations’ performance in IP management. Based on the audit results, organizations will know the strength and weakness of their current IP management practice and can allocate resources and efforts in priority area for improvement. The authors have validated the developed system and tool in HK–Guangdong (HK–GD) based manufacturing organizations with satisfactory outcome. The audit results are helpful to provide top management facts and information to develop action plans for improving IP management. This paper presents the proposed IP audit system and the industrial case study with the development of an expert assessment tool. [Copyright &y& Elsevier]

Abstract: In the scientific literature, one can find different techniques for tackling the problem involved in generating manoeuvres in robots with nonholonomic restrictions. Among these, probabilistic generation methods have been widely used. This paper presents a new technique that enables the best paths to be selected from among a set provided by a probabilistic planning method (RRT). This selection involved the application of multicriteria decision-making techniques (MCDMT). The particularity of these MCDMT lies in the fact that they provide the same result as would arise if the decision had been taken by a human being. The application of these techniques (generation and ranking) has enabled the development of an automatic tool for finding the best manoeuvres for nonholonomic robots. Lastly, we present the application of these techniques to a real situation, obtaining excellent results. [Copyright &y& Elsevier]

Abstract: Outsourcing is a good strategy for firms that need to reduce operating costs and improve competitiveness, but it remains important for firms to scientifically select the appropriate outsourcing providers. Some efforts have been made regarding outsourcing problems, but these efforts incorrectly assumed that the criteria in the decision process are independent, which is not true in the real world. In this paper, we propose a new hybrid multiple criteria decision-making (MCDM) model, which addresses the dependent relationships among criteria with the aid of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to build a relations-structure among criteria. The Analytical Network Process (ANP) is used to determine the relative weights of each criterion with dependence and feedback. The VIKOR method (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, meaning Multi-criteria Optimization and Compromise Solution) is then used to prioritize the alternatives. The proposed model can help practitioners improve their decision process, especially when criteria are numerous and inter-related. Throughout our study, we use data from a Taiwanese airline to demonstrate this method. [Copyright &y& Elsevier]

Abstract: This paper proposes a new multiobjective feature selection approach for churn prediction in telecommunication service field, based on the optimisation approach NSGA-II. The basic idea of this approach is to modify the approach NSGA-II to select local feature subsets of various sizes, and then to use the method of searching nondominated solutions to select the global nondominated feature subsets. Finally, the method FBSM which yields the fitness thresholds is proposed to choose the global solutions with the lowest ranks as the final solutions. In order to evaluate the proposed approach, experiments were carried out and the experimental results show that the proposed feature selection approach is efficient for churn prediction with multiobjectives. [Copyright &y& Elsevier]

Abstract: Critical facility vulnerability assessment is a highly complex strategic activity in combating the terrorism and necessitates a structured quantified methodology to support the decision-making process in defense planning. In the system perspective, the critical facility, such as airport, dam, governmental facility, harbor, nuclear power plant, oil plant etc., can be defined as a system that relies on a group of different interdependent logical and physical entities as system functions and system components. The aim of this paper is to present a realistic approach to determine the vulnerability of such a system defended against the terrorist attack under multiple criteria which can be both qualitative and quantitative by considering these interdependencies. The proposed approach, called fuzzy integrated vulnerability assessment model (FIVAM), is based on fuzzy set theory, Simple Multi-Attribute Rating Technique (SMART) and Fuzzy Cognitive Maps (FCM) methodology in a group decision-making environment. The FIVAM approach is presented step-by-step and applied to a simple case study on airport vulnerability assessment. The results of the application are compared to those observed through a classical vulnerability assessment model to illustrate the effectiveness of the FIVAM. Furthermore, FIVAM provides a framework to identify the hidden vulnerabilities caused by the functional interdependencies within the system. The results also show that FIVAM quantifies the vulnerability of the system, system functions and system components, and determines the most critical functions and components by simulating the system behavior. [Copyright &y& Elsevier]

Abstract: This paper introduces a fuzzy decision support system (FDSS) with a new decision making structure, which can be applied to manage the crisis conditions in any large scale systems with many parameters. After receiving both functional variables of the system and fault signals, the FDSS makes proper decisions to make up and repair the distorted situation and the affected elements of the network according to its data base established through experience gathered from expert managers and decision models properly developed. These decisions are expressed in the form of some scenarios with different desirability degrees, which are determined by some properly developed fuzzy multi-criteria decision making methods, helping the manager choose the best one according to his discretion. [Copyright &y& Elsevier]

Abstract: Nowadays, liner shipping has become a constant operation model for shipping companies, and scheduling is an important issue for operation. It is well-known that a nice plan for route of container ships will bring long-term profit to companies. In the earlier works, the market demand is assumed to be crisp. However, the market demand could be uncertain in real world. Fuzzy sets theory is frequently used to deal with the uncertainty problem. On the other hand, genetic algorithm owns powerful multi-objective searching capability and it can extensively find optimal solutions through continuous copy, crossover, and mutation. Due to these advantages, in this paper, a fuzzy genetic algorithm for liner shipping planning is proposed. This algorithm not only takes market demand, shipping and berthing time of container ships into account simultaneously but also is capable of finding the most suitable route of container ships. [Copyright &y& Elsevier]

Abstract: Transportation network design problem (NDP) is inherently multi-objective in nature, because it involves a number of stakeholders with different needs. In addition, the decision-making process sometimes has to be made under uncertainty where certain inputs are not known exactly. In this paper, we develop three stochastic multi-objective models for designing transportation network under demand uncertainty. These three stochastic multi-objective NDP models are formulated as the expected value multi-objective programming (EVMOP) model, chance constrained multi-objective programming (CCMOP) model, and dependent chance multi-objective programming (DCMOP) model in a bi-level programming framework using different criteria to hedge against demand uncertainty. To solve these stochastic multi-objective NDP models, we develop a solution approach that explicitly optimizes all objectives under demand uncertainty by simultaneously generating a family of optimal solutions known as the Pareto optimal solution set. Numerical examples are also presented to illustrate the concept of the three stochastic multi-objective NDP models as well as the effectiveness of the solution approach. [Copyright &y& Elsevier]

Abstract: In this paper, we consider the flow shop scheduling problem with respect to the both objectives of makespan and total flowtime. This problem is known to be NP-hard type in literature. Several algorithms have been proposed to solve this problem. We present a multi-objective ant colony system algorithm (MOACSA), which combines ant colony optimization approach and a local search strategy in order to solve this scheduling problem. The proposed algorithm is tested with well-known problems in literature. Its solution performance was compared with the existing multi-objective heuristics. The computational results show that proposed algorithm is more efficient and better than other methods compared. [Copyright &y& Elsevier]

Abstract: For most of managers purchasing is a strategic issue. Thus, to select the suitable suppliers has strategic importance for every company. The objective of supplier selection is to reduce purchasing risk, maximize overall value to the purchaser and build a long term, reliable relationship between buyers and suppliers. Many methods have been proposed and used for supplier evaluation and selection; most of them try to rank the suppliers from the best to the worst and to choose the appropriate supplier(s). Supplier evaluation and selection is a complex and typical multi criteria decision-making problem. Because of human judgment needs in many area of supplier selection such as preferences on alternatives or on the attributes of suppliers or the class number and borders supplier selection becomes more difficult and risky. In this study, a new tool for supplier selection is proposed. In this paper, we applied Fuzzy Adaptive Resonance Theory (ART)’s classification ability to the supplier evaluation and selection area. The proposed selection method, using Fuzzy ART not only selects the most appropriate supplier(s) and also clusters all of the vendors according to chosen criteria. To explain the Fuzzy ART method a real-life supplier selection problem is solved and suppliers are categorized according to their similarities. The obtained results show that the proposed method is well suited as a decision-making tool for supplier evaluation and selection problem. [Copyright &y& Elsevier]

Abstract: Most previous research into the job-shop scheduling problem has concentrated on finding a single optimal solution (e.g., makespan), even though the actual requirement of most production systems requires multi-objective optimization. The aim of this paper is to construct a particle swarm optimization (PSO) for an elaborate multi-objective job-shop scheduling problem. The original PSO was used to solve continuous optimization problems. Due to the discrete solution spaces of scheduling optimization problems, the authors modified the particle position representation, particle movement, and particle velocity in this study. The modified PSO was used to solve various benchmark problems. Test results demonstrated that the modified PSO performed better in search quality and efficiency than traditional evolutionary heuristics. [Copyright &y& Elsevier]

Abstract: Although environment watershed plans have management and erosion control plans, public perception often focuses excessively on catastrophes. Environment plans are affected by many factors such as human life, property, safety, management, operations, maintenance, ecology, the environment, artificial structures, and climate control. The purpose of this paper is to qualitatively and quantitatively measure the environment watershed plan indexes and to achieve the aspired levels for these plan indexes. Previous efforts to evaluate the environment plans have assumed that the criteria are independent, but reality proves otherwise. Here, we use a novel hybrid multiple criteria decision-making (MCDM) model to address the dependent relationships among the criteria. Specifically, we combined the decision-making trial and evaluation laboratory model (DEMATEL) with the analytical network process (ANP) to calculate the relative weights of the criteria under interdependence and feedback. A real-life environment watershed problem is investigated to demonstrate the proposed novel hybrid MCDM model. We also propose a strategy to improve the criteria gaps for achieving the aspired levels for human life and safety. [Copyright &y& Elsevier]

Abstract: Supplier selection is a critical and demanding task for companies that participate in electronic marketplaces to find suppliers and to execute electronically their transactions. This paper is aimed to suggest a fresh approach for decision support enabling effective supplier selection processes in electronic marketplaces. We introduce an evaluation method with two stages: initial screening of the suppliers through the enforcement of hard constraints on the selection criteria and final supplier evaluation through the application of a modified variant of the Fuzzy Preference Programming (FPP) method. The proposed method alleviates the information overload effect that is inherent in the environment of electronic marketplaces, facilitates an easier elicitation of user preferences through the reduction of necessary user input (i.e. pairwise comparisons) and reduces computational complexity, in terms of the number of linear programs to be solved, in comparison with the original FPP method. The FPP method is adopted and modified accordingly in order to tackle the issue of inconsistency/uncertainty of human preference models. Our approach is demonstrated with the example of a hypothetical metal manufacturing company that finds and selects suppliers in the environment of an electronic marketplace. [Copyright &y& Elsevier]

Abstract: During recent years, how to determine suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of supplier selection is a complex multi-criteria problem including both quantitative and qualitative factors which may be in conflict and may also be uncertain. The VIKOR method was developed to solve multiple criteria decision making (MCDM) problems with conflicting and non-commensurable (different units) criteria, assuming that compromising is acceptable for conflict resolution, the decision maker wants a solution that is the closest to the ideal, and the alternatives are evaluated according to all established criteria. In this paper, linguistic values are used to assess the ratings and weights for these factors. These linguistic ratings can be expressed in trapezoidal or triangular fuzzy numbers. Then, a hierarchy MCDM model based on fuzzy sets theory and VIKOR method is proposed to deal with the supplier selection problems in the supply chain system. A numerical example is proposed to illustrate an application of the proposed model. [Copyright &y& Elsevier]

Wear and corrosion are the most important factors that the surface of the engineering parts must confront. The need for protection and improvement of the mechanical characteristics of the surface of engineering parts can be to some extent satisfied by coatings. Coatings are considered as an excellent solution when resistance to corrosion, oxidation or low friction is demanded, but due the complexity of selecting the appropriate one, engineers often avoid them. The need for simultaneous consideration of qualitative and quantitative properties, render the use of classic material selection theories inadequate. An expert system for coating selection is presented in this paper, which can handle both qualitative and quantitative variables. The mathematical model used combines the multi-criteria decision making theories (MCDM) together with the fuzzy sets theory. The ¿Max-Min set¿ method is applied to calculate the ordering value of the alternatives while the TOPSIS method is used to rank them. A numerical example is provided to illustrate the method. Finally, the process presented can be easily computerized, to create the relative software. [Copyright &y& Elsevier]

In this paper the state-of-the-art extended particle swarm optimization (PSO) methods for solving multi-objective optimization problems are represented. We emphasize in those, the co-evolution technique of the parallel vector evaluated PSO (VEPSO), analysed and applied in a multi-objective problem of steady-state of power systems. Specifically, reactive power control is formulated as a multi-objective optimization problem and solved using the parallel VEPSO algorithm. The results on the IEEE 30-bus test system are compared with those given by another multi-objective evolutionary technique demonstrating the advantage of parallel VEPSO. The parallel VEPSO is also tested on a larger power system this with 136 busses. [Copyright &y& Elsevier]

In current practice, the design is still based on the sequential design methodology, which makes the process or manufacture information not considered at the preliminary design stage. In addition, the quality of design and the time to perform them are largely dependent on the experience of the engineers. Case-based design is an intelligent method which involves retrieving the most similar previous cases to provide a solution of a new decision problem. Therefore, case retrieval is the most crucial process in case-based design. However, few studies attempt to research case retrieval in concurrent design. This paper proposes a hybridization of fuzzy similarity measurement (FSM) and fuzzy multi-criteria decision making (FMCDM) for case retrieval from historical cases for concurrent design. In FSM stage, triangular function is used to represent the different fuzzy requirements, respectively, and meanwhile calculate the similarity. Less valuable case is filtered out by defined threshold. Then FMCDM is developed to evaluate the most similar cases in terms of product criteria to pick out the most suitable case. Furthermore, the FSM–FMCDM model is applied to power transformer concurrent design, and the experiment indicates that the FSM–FMCDM retrieval is more reasonable than the prior SM only case retrieval. [Copyright &y& Elsevier]

The paper proposed a Fuzzy Multiple Criteria Decision Making (FMCDM) approach for banking performance evaluation. Drawing on the four perspectives of a Balanced Scorecard (BSC), this research first summarized the evaluation indexes synthesized from the literature relating to banking performance. Then, for screening these indexes, 23 indexes fit for banking performance evaluation were selected through expert questionnaires. Furthermore, the relative weights of the chosen evaluation indexes were calculated by Fuzzy Analytic Hierarchy Process (FAHP). And the three MCDM analytical tools of SAW, TOPSIS, and VIKOR were respectively adopted to rank the banking performance and improve the gaps with three banks as an empirical example. The analysis results highlight the critical aspects of evaluation criteria as well as the gaps to improve banking performance for achieving aspired/desired level. It shows that the proposed FMCDM evaluation model of banking performance using the BSC framework can be a useful and effective assessment tool. [Copyright &y& Elsevier]