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Highlights • A data mining method for topology optimization is proposed. • The method sequentially applies clustering and association rule analysis. • A distance measure for pairs of configurations is defined. • Confidence and lift indexes in multiobjective topology optimizations are defined. • The method is applied in 3- and 4-objective design problems in 2 and 3 dimensions. Abstract Optimum design problems, including structural optimization problems, often include multiple objectives. A multiobjective optimization problem usually provides a number of optimal solutions, called non-dominated solutions or Pareto-optimal solutions. In multiobjective topology optimization scenarios, decision makers face the challenging task of choosing the most effective solution that meets their needs; serial comparisons among a set of Pareto-optimal solution are cumbersome, as are trial-and-error attempts to find an appropriate solution among a host of alternatives. On the other hand, the recent integration of data mining techniques in multiobjective optimization methods can provide decision makers with important, highly pertinent, and useful knowledge. In this paper, we propose a data mining technique for knowledge discovery in multiobjective topology optimization. The proposed method sequentially applies clustering and association rule analysis to a Pareto-optimal solution set. First, clustering is applied in the design space and the result is then visualized in the objective space. After clustering, detailed features in each cluster are analyzed based on the concept of association rule analysis, so that characteristic substructures can be extracted from each cluster of solutions. In four numerical examples, we demonstrate that the proposed method provides pertinent knowledge that aids comprehension of the key substructures responsible for one or more desired performances, thereby giving decision makers a useful tool for discovery of particularly effective design solutions. [ABSTRACT FROM AUTHOR]

Abstract: In the present paper, a novel fuzzy Multiple Attribute Decision Making (MADM) model is proposed for modeling and solving truck selection problem of a land transportation company. As truck selection is a very crucial problem for the land transportation companies, a systematic and scientific approach is necessary for its solution. A systematic methodology is proposed in the present study by integrating “fuzzy DEMATEL” and “fuzzy hierarchical TOPSIS”. The proposed method makes use of fuzzy DEMATEL method for evaluating the weights of the criteria and hierarchical fuzzy TOPSIS method for assessing the alternatives according to criteria. The steps of the method are described first then a case study is presented in the paper. [Copyright &y& Elsevier]

Abstract: In this paper we present a new approach to solve multi-attribute decision making problems in intuitionistic fuzzy environment. This approach is based on a new ranking method of intuitionistic fuzzy sets, in which the evaluated values (in the form of intervals) of the same alternative with different attributes are considered as one unified entity. According to people’s intuition, the ranking method proposed in this paper is mainly grounded on a revised score function and a revised accuracy function of intuitionistic fuzzy sets. Different from the traditional methods, in this new approach, the degree of membership, the degree of nonmembership and the degree of hesitation are considered with various importance in reflecting the true image of the respective alternative. Furthermore, an optimization model is established to estimate the relative degree of importance of each quantity. Finally, two practical examples are provided to illustrate our approach. [Copyright &y& Elsevier]

Abstract: In this paper the authors review the developments of the analytic hierarchy process (AHP) since its inception. The focus of this paper is a neutral review on the methodological developments rather than reporting its applications that have appeared since its introduction. In particular, we discuss problem modelling, pair-wise comparisons, judgement scales, derivation methods, consistency indices, incomplete matrix, synthesis of the weights, sensitivity analysis and group decisions. All have been important areas of research in AHP. [Copyright &y& Elsevier]

Abstract: Supply planning of two-level assembly system is considered in this paper in which lead times are stochastic at both levels. Finding optimal order release dates of components is our aim which optimizes problem’s performance metrics. There is a determined due date that if demands are not prepared for delivery in that day, backlogging cost would happen. The other noticeable cost that should be taken in to consideration is holding cost, which may occur if components arrive before their time of assembling. In contrast to most of studies in this field that consider sum of these cost, this paper attempts to make a tradeoff between these objectives’ affects using multi-objective approach. This approach hybridizes an evolutionary optimizer, genetic algorithm, with an electromagnetism-like mechanism (EM). The algorithm’s effectiveness is compared against an adapted non-dominated sorting genetic algorithm II (NSGA-II) which has been presented for this problem. [Copyright &y& Elsevier]

Abstract: In a recent paper by Toloo et al. [Toloo, M., Sohrabi, B., & Nalchigar, S. (2009). A new method for ranking discovered rules from data mining by DEA. Expert Systems with Applications, 36, 8503–8508], they proposed a new integrated data envelopment analysis model to find most efficient association rule in data mining. Then, utilizing this model, an algorithm is developed for ranking association rules by considering multiple criteria. In this paper, we show that their model only selects one efficient association rule by chance and is totally depended on the solution method or software is used for solving the problem. In addition, it is shown that their proposed algorithm can only rank efficient rules randomly and will fail to rank inefficient DMUs. We also refer to some other drawbacks in that paper and propose another approach to set up a full ranking of the association rules. A numerical example illustrates some contents of the paper. [Copyright &y& Elsevier]

Abstract: Multiple criteria decision-making (MCDM) research has developed rapidly and has become a main area of research for dealing with complex decision problems. The purpose of the paper is to explore the performance evaluation model. This paper develops an evaluation model based on the fuzzy analytic hierarchy process and the technique for order performance by similarity to ideal solution, fuzzy TOPSIS, to help the industrial practitioners for the performance evaluation in a fuzzy environment where the vagueness and subjectivity are handled with linguistic values parameterized by triangular fuzzy numbers. The proposed method enables decision analysts to better understand the complete evaluation process and provide a more accurate, effective, and systematic decision support tool. [ABSTRACT FROM AUTHOR]

Decision on alternative-fuel vehicles is one of the most important problems for fleet operations. In this paper we propose a hierarchical hesitant fuzzy linguistic model that captures hesitant linguistic evaluations of multiple experts on multiple criteria for alternative-fuel vehicles. We apply the proposed model on the alternative-fuel vehicle selection problem of a home health care service provider in the USA. The results show that an electric vehicle is the best fit for the application in today’s conditions. We also show robustness of the decision through a sensitivity analysis as well as analyze three scenarios representing possible changes in conditions. [ABSTRACT FROM AUTHOR]

Abstract: Supplier selection is an important issue in supply chain management (SCM), and essentially is a multi-criteria decision-making problem. Supplier selection highly depends on experts’ assessments. In the process of that, it inevitably involves various types of uncertainty such as imprecision, fuzziness and incompleteness due to the inability of human being’s subjective judgment. However, the existing methods cannot adequately handle these types of uncertainties. In this paper, based on a new effective and feasible representation of uncertain information, called D numbers, a D-AHP method is proposed for the supplier selection problem, which extends the classical analytic hierarchy process (AHP) method. Within the proposed method, D numbers extended fuzzy preference relation has been involved to represent the decision matrix of pairwise comparisons given by experts. An illustrative example is presented to demonstrate the effectiveness of the proposed method. [Copyright &y& Elsevier]

Abstract: The aim of the present paper is to optimize and extend the recent method in . We simplify the calculus taking into account the expected value of a fuzzy number can be expressed by using its α-cut sets. A collateral benefit is that the discussed method becomes applicable in any structure of data as triangular fuzzy numbers. Then, to cover a wider range of data – performances of alternatives versus criteria and importance weights of criteria – we extend the optimized method to trapezoidal fuzzy numbers and to the cases of importance weights of criteria/ratings of alternatives expressed by real numbers and ratings of alternatives/importance weights of criteria expressed by fuzzy numbers. Each theoretical development is illustrated by examples. The importance of the method to the selection of the best touristic destinations is discussed too. [Copyright &y& Elsevier]

Abstract: The aim of this paper is to develop a regime switching design of the fuzzy analytic hierarchy process (FAHP) and to improve its functionality under the choice-varying priority (CVP) problem. In the conventional AHP decision process, priority matrices are identical and their values are invariant for a specific objective. However, in many Multi-Criteria Decision Making (MCDM) problems, the relative importance of criteria may differ according to the choices. A regime switching process is proposed for improving the CVP problem. Under the fuzzy-AHP (FAHP) framework, choice-varying priorities are presented in a cubic matrix form. Another novel contribution is suggested in the prioritization of the level of expert consistency. During the decision-making practice, experts may have different attitudes and their individual matrix consistencies might be superior or inferior in their overall practices. Individual consistency is one of the objective indicators of the quality of judgment. An expert consistency prioritization approach is proposed to deal with the classification of response stability. For the financial risk assessment part of the study, the loss probability of the intended projects is calculated by the fuzzy Monte-Carlo simulation framework. [Copyright &y& Elsevier]

Abstract: Supplier selection is usually involved a multi-criteria evaluation to assist decision-making. This study proposed a simple method for vendor selection. The proposed procedure utilizes the structure of criteria in analytic hierarchy process (AHP) model and employs consistent fuzzy preference relations (CFPR) to construct the decision matrices. The advantage of CFPR is computational simplicity and efficiency. The computation can be done by using an Excel spreadsheet or writing a simple computer program. Also, the CFPR method guarantees the consistency of decision matrices. In this paper, a step-by-step empirical example demonstrates the usage of this proposed method. [Copyright &y& Elsevier]

Abstract: It is well known that “green” principles and strategies have become vital for companies as the public awareness increased against their environmental impacts. A company’s environmental performance is not only related to the company’s inner environmental efforts, but also it is affected by the suppliers’ environmental performance and image. For industries, environmentally responsible manufacturing, return flows, and related processes require green supply chain (GSC) and accompanying suppliers with environmental/green competencies. During recent years, how to determine suitable and green suppliers in the supply chain has become a key strategic consideration. Therefore this paper examines GSC management (GSCM) and GSCM capability dimensions to propose an evaluation framework for green suppliers. 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 identified components are integrated into a novel hybrid fuzzy multiple criteria decision making (MCDM) model combines the fuzzy Decision Making Trial and Evaluation Laboratory Model (DEMATEL), the Analytical Network Process (ANP), and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) in a fuzzy context. A case study is proposed for green supplier evaluation in a specific company, namely Ford Otosan. [Copyright &y& Elsevier]

Abstract: Distribution channel management not only consists of choosing distribution channels. In fact, probably the most difficult phase of the distribution management starts after this choice. Determining an appropriate organization strategy for distribution channel management is like a problem of concern to marketing practitioners and academics as well in this phase. In this study, the organization strategy of distribution channel management is developed using fuzzy analytic hierarchy process (FAHP) and hierarchical fuzzy TOPSIS (HFTOPSIS) for an edible-vegetable oils manufacturer firm operating in Turkey. The company distributes its products all over the country. Due to the complex structure of the distribution network, the company wants to decide the organization strategy to manage the distribution channels. In this paper, the methods of FAHP and HFTOPSIS for evaluating and selecting among the five organization strategy models for distribution channel management of vegetable oil manufacturer have been presented. The proposed models include determinants of distribution channel management for edible-vegetable oil industry; (i) customer profile, (ii) distributor reliability, (iii) the position of competitors in market, and (iv) managerial and financial perspective. Using FAHP and HFTOPSIS, hybrid based strategy (KBS), which has the greatest desirability index value after the evaluation among the five alternatives is found as the best choice. Thus, the case of the vegetable oil manufacturer company provides the researchers and practitioners to understand in a better way the importance of developing organization strategy in channel management from a practical point of view. [Copyright &y& Elsevier]

Abstract: In order to improve the quality of decision about orders incoming to make to order (MTO) company, an effective evaluation approach is essential. So, in this paper a comprehensive decision making structure is presented for acceptance or rejection of incoming orders. The aim of the proposed structure is to manage the arriving orders so that the MTO system just proceeds to produce those arriving orders which are feasible and profitable for the system. The proposed structure composed of three phases. At the first phase, arriving orders are prioritized into high and low priority orders, considering characteristics of order and customer and utilizing technique for order performance by similarity to ideal solution (TOPSIS). At the second phase, rough-cut capacity was calculated for each order regarding priority level and so, acceptance or rejection decision is taken based on it. Finally, at the third phase, the previous phase accepted orders are evaluated based on their due dates and material arrival times and final decisions for orders are made. At the end, the effectiveness of the proposed structure is demonstrated through a case study. [Copyright &y& Elsevier]

Abstract: In this paper we address the problem of music playlist generation based on the user-personalized specification of context information. We propose a generic semantic multicriteria ant colony algorithm capable of dealing with domain-specific problems by the use of ontologies. It also employs any associated metadata defined in the search space to feed its solution-building process and considers any restrictions the user may have specified. An example is given of the use of the algorithm for the problem of automatic generation of music playlists, some experimental results are presented and the behavior of the approach is explained in different situations. [Copyright &y& Elsevier]

Abstract: Weapon System Capability Assessment (WSCA) is the initial point of quantification of capabilities in the military capability planning (MCP). WSCA is often a multiple criteria decision making (MCDM) problem with both quantitative and qualitative information under uncertain environment. In this paper, the analysis process and algorithm for WSCA problem is proposed on the basis of belief structure (BS) model and evidential reasoning (ER) approach which were developed to deal with various types of uncertainties such as ignorance and subjectiveness. First of all, the WSCA criteria hierarchy is built by analyzing how the capability is measured. Secondly, a weapon system capability model is formulated using BS. Thirdly, both qualitative and quantitative information involved in capability measure are transformed into BSs by the data transformation algorithm based on rules. Then, the analytical ER approach is used to aggregate the capability measurement information from sub-capability criteria to top-capability criterion, and the assessed weapon systems are ranked and analyzed according to utility intervals. Finally, a case study of real Main Battle Tank capability assessment is explored to show the proposed process for WSCA. [Copyright &y& Elsevier]

Abstract: Decision making is the process of finding the best option among the feasible alternatives. In classical multiple-criteria decision making methods, the ratings and the weights of the criteria are known precisely. However, if decision makers are not able to involve uncertainty in the defining of linguistic variables based on fuzzy sets, the intuitionistic fuzzy set theory can do this job very well. In this paper, VIKOR method is extended in intuitionistic fuzzy environment, aiming at solving multiple-criteria decision making problems in which the weights of criteria and ratings of alternatives are taken as triangular intuitionistic fuzzy set. For application and verification, this study presents a robot selection problem for material handling task to verify our proposed method. [Copyright &y& Elsevier]

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: 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: 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: 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 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: 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 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: 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: 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: 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: 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]

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]

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]

To deal with complex problems, structuring them through graphical representations and analyzing causal influences can aid in illuminating complex issues, systems, or concepts. The DEMATEL method is a methodology which can confirm interdependence among variables and aid in the development of a chart to reflect interrelationships between variables, and can be used for researching and solving complicated and intertwined problem groups. The end product of the DEMATEL process is a visual representation—the impact-relations map—by which respondents organize their own actions in the world. In order to obtain a suitable impact-relations map, an appropriate threshold value is needed to obtain adequate information for further analysis and decision-making. In the existing literature, the threshold value has been determined through interviews with respondents or judged by the researcher. In most cases, it is hard and time-consuming to aggregate the respondents and make a consistent decision. In addition, in order to avoid subjective judgments, a theoretical method to select the threshold value is necessary. In this paper, we propose a method based on the entropy approach, the maximum mean de-entropy algorithm, to achieve this purpose. Using a real case to find the interrelationships between the services of a Semiconductor Intellectual Property Mall as an example, we will compare the results obtained from the respondents and from our method, and show that the impact-relations maps from these two methods could be the same. [Copyright &y& Elsevier]

Abstract: Bancassurance has enjoyed considerable success in Europe, but this concept is relatively new for Asian countries, having emerged only in 2002. Thus, the aim of this paper is to search and identify the preferable bancassurance alliance structure from the executive management perspectives. We adopt the analytical hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to construct an evaluation method. Finally, this study proves that Financial Holding Company model in bancassurance alliance models is preferable for the executive. [Copyright &y& Elsevier]

Abstract: To support the efficient appraisal of and selection from a list of generic business process improvement principles, this paper proposes a strategy for the implementation of business process redesign (BPR). Its backbone is formed by the analytic hierarchy process (AHP) multicriteria method and our earlier research into the popularity and impact of a set of redesign “best practices”. Using AHP, we derive a classification of most suitable directions for a particular process to be redesigned. Criteria such as the popularity, the impact, the goals and the risks of BPR implementation are taken into account. A case study is included to demonstrate the method’s feasibility and effectiveness. [Copyright &y& Elsevier]

Abstract: Asian travel industry, in terms of outbound travel markets, has been confronting the global accelerating competition in 21st century. Regarding to the outbound travels, the incumbent travel intermediaries (destination tour operators), the ultimate front-liners of tourism packages provisions is accordingly essential. Technically, estimation on the incumbent travel intermediaries is a series of multiple-criteria decision making (MCDM). Subsequently, this paper executes the implementation of focus group which interviewed 35 travel experts and further integrates the analytic network process approach (ANP) via the insights of host travel agency. Research results objectively enable the Asian travel agencies to evaluate the sustained travel intermediary as well as elaborating the service performance and quality. [Copyright &y& Elsevier]

Abstract: For ensuring the successful implementation of medical service investments, here an expert selection system of how ventures can better evaluate and select a favorable city to invest before that implementation has been developed. However, selecting an ideas city is a kind of multiple criteria decision-making (MCDM) problem requiring to consider a large number of complex factors that are based on the independence assumption. The analytic network process (ANP) is a relativly new MCDM method which can deal with all kinds of dependences systematically. With the advantages of ANP in hand, in this paper, we develop an effective method based on the ANP combined with the technique for order preference by similarity to ideal solution (TOPSIS) to help medical service inventors who need to evaluate and select proper city. Additionally, an empirical study is presented to illustrate the application of the proposed method. [Copyright &y& Elsevier]

This paper presents a multiple criteria decision approach for trading weekly tool capacity between two semiconductor fabs. Due to the high-cost characteristics of tools, a semiconductor company with multiple fabs (factories) may weekly trade their tool capacities. That is, a lowly utilized workstation in one fab may sell capacity to its highly utilized counterpart in the other fab. Wu and Chang [Wu, M. C., & Chang, W. J. (2007). A short-term capacity trading method for semiconductor fabs with partnership. Expert Systems with Application, 33(2), 476–483] have proposed a method for making weekly trading decisions between two wafer fabs. Compared with no trading, their method could effectively increase the two fabs’ throughput for a longer period such as 8weeks. However, their trading decision-making is based on a single criterion—number of weekly produced operations, which may still leave a space for improving. We therefore proposed a multiple criteria trading decision approach in order to further increase the two fabs’ throughput. The three decision criteria are: number of operations, number of layers, and number of wafers. This research developed a method to find an optimal weighting vector for the three criteria. The method firstly used NN+GA (neural network+genetic algorithm) to find an optimal trading decision in each week, and then used DOE+RSM (design of experiment+response surface method) to find an optimal weighting vector for a longer period, say 10weeks. Experiments indicated that the multiple criteria approach indeed outperformed the previous method in terms the fabs’ long-term throughput. [Copyright &y& Elsevier]