Fuzzy Multiple Criteria Decision Making Problems Research Articles

Hesitant Fuzzy Linguistic Possibility Degree-Based Linear Assignment Method for Multiple Criteria Decision-Making

Hesitant fuzzy linguistic term set (HFLTS), as a flexible tool to represent people’s uncertain cognition, has attracted lots of scholars’ research interests, and a series of methodologies have been proposed to deal with a variety of decision-making problems. In this paper, we develop a hesitant fuzzy linguistic possibility degree-based linear assignment (HFL-PDLA) method to tackle the multiple criteria decision-making (MCDM) problems under hesitant fuzzy linguistic environment. Firstly, we define the possibility degree of hesitant fuzzy linguistic element (HFLE). Additionally, some relevant concepts related to the HFL-PDLA method are proposed, such as the relative difference matrix, the rank contribution matrix, the optimal permutation matrix, etc. Furthermore, the algorithm of the HFL-PDLA method is given to deal with hesitant fuzzy linguistic MCDM problems. Moreover, we apply the HFL-PDLA method to deal with a practical case which is to select the optimal treatment technology for disposing the outspent or old medical apparatuses and instruments in West China Hospital (WCH). Finally, we show the advantages of the HFL-PDLA method by making some comparative analyses with the TOPSIS method, the VIKOR method the PROMETHEE method and the LINMAP method.

Alternative queuing method for multiple criteria decision making with hybrid fuzzy and ranking information

Multiple criteria decision making (MCDM), concerning the selection of the most optimal alternative(s), is an essential activity in various fields of management science. In many practical MCDM problems, it is common that there are different types of fuzzy evaluation information as well as ranking information on candidate alternatives with respect to different criteria. In this paper, we propose an alternative queuing method (AQM) to deal with this kind of hybrid fuzzy MCDM problems. Firstly, we develop an algorithm of the AQM to solve the hybrid fuzzy MCDM problems in which the criteria weights are completely known. Secondly, we propose a satisfaction degree based method to derive the criteria weights for the hybrid fuzzy MCDM problems in which the weight information is partly known, and then use the developed algorithm to further solve this kind of problems. Thirdly, we propose a least square method to derive the criteria weights for the hybrid fuzzy MCDM problems in which the weight information is completely unknown. Finally, we apply the AQM to select the optimal treatment technology for disposing the outspent or old medical apparatuses and instruments in West China Hospital.

A Hybrid Method for Pythagorean Fuzzy Multiple-Criteria Decision Making

As a generalization of intuitionistic fuzzy set, the Pythagorean fuzzy set is interesting and very useful in modeling uncertain information in real-world decision-making problems. In this paper, we develop a new method for Pythagorean fuzzy multiple-criteria decision-making (MCDM) problems with aggregation operators and distance measures. First, we present the Pythagorean fuzzy ordered weighted averaging weighted average distance (PFOWAWAD) operator. The main advantage of the PFOWAWAD operator is that it uses distance measures in a unified framework between the ordered weighted averaging (OWA) operator and weighted average (WA) that considers the degree of importance of each concept in the aggregation. Some of its main properties and special cases are studied. Then, based on the proposed operator, a hybrid TOPSIS method, called PFOWAWAD-TOPSIS is introduced for Pythagorean fuzzy MCDM problem. Finally, a numerical example is provided to illustrate the practicality and feasibility of the developed method.

A decision support system for IMS selection based on fuzzy VIKOR method

Intelligent manufacturing system (IMS) presents system with autonomous ability to adapt to unexpected changes. In order to succeed in this ever so demanding, fast pace business environment, managers need integrated and IMS capable of supporting them throughout the decision-making lifecycle. Therefore, it is worthwhile to invest on making appropriate decisions on IMS selection. The selecting process mainly involves evaluation of different alternatives based on different criteria. This process is essentially considered as a multiple criteria decision-making (MCDM) problem which is affected by different tangible and intangible criteria including price, quality, performance, lead-time, efficiency, etc. This paper presents a model based on VIKOR method to select an appropriate IMS. Based on the concept of fuzzy logic and the VIKOR method, the proposed fuzzy VIKOR method has been developed to provide a rational and systematic process. The proposed method can be used to find a best solution to resolve a fuzzy MCDM problem and to specify the preferred solution for any decision problem in real organisational set up.

A new flexible and reliable interval valued fuzzy VIKOR method based on uncertainty risk reduction in decision making process: An application for determining a suitable location for digging some pits for municipal wet waste landfill

Facility location selection problem is one of the challenging and famous kinds of MCDM problems including both quantitative and qualitative criteria. For each Multiple Criteria Decision Making (MCDM) problem, when the ratings of alternatives with respect to the criteria and/or the values of criteria’s weights are presented by Interval Valued Fuzzy Numbers (IVFNs), the conventional fuzzy MCDM methods (Type-1 fuzzy MCDM methods) tend to be less effective. Therefore, the IVF-MCDM (Interval Valued Fuzzy MCDM) methods should be applied for solving such fuzzy MCDM problems. In this paper, we propose an IVF-VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method based on uncertainty risk reduction in decision making process. By using such method, the reliability of the captured decisions in an IVF decision making problem is significantly increased. The proposed method is applied for solving two numerical examples that the former of which is a real application problem related to selecting a suitable location for digging some pits for municipal wet waste landfill in one of the largest cities in Iran. The second numerical example is presented with an aim of comparing our method with the two other IVF-MCDM methods. As a result, we found out the proposed method is reliable and practical for the facility location selection problems and other MCDM problems. Moreover, the proposed method has a considerable accuracy and is flexible and easy to use.

A new flexible and reliable IVF-TOPSIS method based on uncertainty risk reduction in decision making process

One of the challenging and famous types of MCDM (Multiple Criteria Decision Making) problems that includes both quantitative and qualitative criteria is Facility location selection problem. For the common fuzzy MCDM problems (Type-1 fuzzy MCDM problems), the ratings of alternatives with respect to the criteria or/and the values of criteria weights, are expressed by the common fuzzy numbers. However, in the majority of cases, determining the exact membership degree for each element of the fuzzy sets which are considered for the ratings of alternatives with respect to the criteria or/and the values of criteria weights as a number in interval [0,1], is difficult. In this situation, the ratings of alternatives with respect to the criteria or/and the values of criteria weights, are expressed by the IVFNs (Interval Valued Fuzzy Numbers) and thereby the IVF-MCDM (Interval Valued Fuzzy MCDM) methods should be used. In this paper, the authors propose an IVF-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method based on uncertainty risk reduction in decision making process. By using this method, the reliability of the captured decisions in an IVF decision making problem is significantly increased. The proposed method is applied for solving a real application problem related to selecting a suitable location for digging some pits for municipal wet waste landfill in one of the largest cities in Iran. The proposed method is also compared with another IVF-TOPSIS method. As a result, the authors concluded that in addition to benefits such as simplicity and ease of use that exist in the previous IVF-TOPSIS methods, the proposed method has a significant reliability and flexibility and is practical for facility location selection problems and other IVF-MCDM problems.

Fuzzy Multiple Criteria Decision Making Model with Fuzzy Time Weight Scheme

In this study, we purpose a common fuzzy multiple criteria decision making model. A brand new concept - fuzzy time weighted scheme is adopted for considering in the model to establish a fuzzy multiple criteria decision making with time weight (FMCDMTW) model. A real case of fuzzy multiple criteria decision making (FMCDM) problems to be considering in this study. The performance evaluation of auction websites based on all criteria proposed in related literature. Obviously, the problem under investigated is a FMCDM problem with historic data and recent data. Since the evaluated criteria proposed in the literature cannot be defined precisely and numerically, fuzzy linguistic terms can be used to aggregate them numerically. It not only conforms to human cognition but also benefits interpretation. Furthermore, notice that the literature considered contains certain amount of historic data. Equally weighted historic data is usually considered in FMCDM problems, and this approach would introduce bias owing to the collected data for a certain long time period. As a result, fuzzy time weighted technique is adopted to resolve this issue. DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.3540 Full Text: PDF

A new fuzzy TOPSIS method based on left and right scores: An application for determining an industrial zone for dairy products factory

The selection of a facility location among alternative locations is a multiple criteria decision making (MCDM) problem including both quantitative and qualitative criteria. In more cases, in real word situations, determining the exact values for MCDM problems and especially for facility location selection problems is difficult or impossible. So, the values of alternatives with respect to the criteria or/and the values of criteria weights, are considered as fuzzy values (fuzzy numbers) so that the conventional crisp approaches for solving facility location selection problems and other MCDM problems tend to be less effective for dealing with the imprecise or vagueness nature of the linguistic assessments. In such conditions, the fuzzy MCDM methods are applied for solving facility location selection problem and other fuzzy MCDM problems. In this paper, we propose a new fuzzy TOPSIS method based on left and right scores for solving fuzzy MCDM problems. We apply the proposed method for solving three numerical examples. The first two numerical examples are proposed for the purpose of comparison. The third numerical example is a real application in which the selection is an industrial zone among several industrial zones for constructing dairy products factory. As a result, we found that the proposed method is practical for solving facility location selection problem and other fuzzy MCDM problems. Moreover, it seems that the proposed fuzzy TOPSIS method is flexible and easy to use and has acceptable accurate.

A new fuzzy weighted average (FWA) method based on left and right scores: An application for determining a suitable location for a gas oil station

The selection of a facility location from alternative locations is a multiple criteria decision making (MCDM) problem including both quantitative and qualitative criteria. In many real-life cases, determining the exact values for MCDM problems, and especially for facility location selection problems, is difficult or impossible, so the values of alternatives with respect to the criteria or/and the values of criteria weights are considered as fuzzy values (fuzzy numbers) such that the conventional crisp approaches for solving facility location selection problems and other MCDM problems tend to be less effective for dealing with the imprecise or vagueness nature of the linguistic assessments. In such conditions, fuzzy MCDM methods are applied for facility location selection problem and other fuzzy MCDM problems. In this paper, we propose a new fuzzy weighted average (FWA) method based on left and right scores for fuzzy MCDM problems. Moreover, we apply the proposed method to a real application. As a result, we found that the proposed method is practical for facility location selection problems. Besides, it seems that the proposed FWA method is very accurate, flexible, simple, and easy to use when compared to other versions of the FWA method.

Optimal location selection for an international distribution center by using a new hybrid method

Research highlights? Location selection problems often involve a complex multicriteria decision process in which multiple requirements and uncertain conditions have to be taken into consideration simultaneously. ? These criteria often exist simultaneously as independent and dependent characteristics. ? This paper proposes a novel hybrid method combining the concepts of fuzzy DEMATEL and a new fuzzy MCDM method in a fuzzy environment is proposed to solve the problems of location selection. ? An empirical case of location selection can demonstrate that the proposed method is an effective means for tackling complex fuzzy MCDM problems. The selection of a location for an international distribution center (IDC) is a most important decision for international logistics managers owing to the need to consider various criteria that involve a complex decision process in which multiple requirements and uncertain conditions have to be taken into consideration simultaneously. Moreover, the criteria often exist simultaneously as independent and dependent characteristics when the problems of location selection have become very complex. A new hybrid method combining the concepts of fuzzy DEMATEL and a new method of fuzzy multiple criteria decision-making (MCDM) in a fuzzy environment is proposed to solve the problems of IDC location selection. In this paper, the fuzzy DEMATEL is proposed to arrange a suitable structure between criteria, and the analytic hierarchy/network process (AHP/ANP) is used to construct weights of all criteria. The linguistic terms characterized by triangular fuzzy numbers are used to denote the evaluation values of all alternatives versus various criteria. Finally, the aggregation fuzzy assessments of different alternatives are ranked to determine the best selection. Furthermore, this paper uses an empirical case for optimal location selection for an IDC in Pacific Asia to illustrate the proposed method, and the results show that the method is an effective means for tackling fuzzy MCDM problems.

A fuzzy multi-criteria model for the industrial cooperation program transaction strategies: A case in Taiwan

In international trade offset practices (in Taiwan known as industrial cooperation program, ICP) have received increased attention over the past 20 years. In the coming 10 years, the Taiwanese government may expend roughly US$16 billion for purchasing Patriot-III missiles, P-3 long-range anti-submarine planes, and diesel-engine submarines from the United States through foreign military sale, and can achieve US$8 billion ICP credit the largest in Taiwanese history. Offsets or ICP can be regarded as fuzzy multiple criteria decision-making (MCDM) problems, therefore, the fuzziness and uncertainty of subjective perception should be considered. This paper provides an alternative approach, the non-additive fuzzy integral, to deal with the fuzzy MCDM problems especially when there is dependence among considered criteria. The main purpose of this paper is to discuss with Taiwan's ICP Optimal Offset Transaction Policy and propose a framework of drawing on ICP credit in future. This paper considers the four aspects of policy, ability, economy, and environment, to establish a set of fuzzy AHP multiple criteria decision mode to identify the evaluative criteria variables and project item's order for ICP project. This decision mode was identified as a workable method.

Combining grey relation and TOPSIS concepts for selecting an expatriate host country

As international corporate activities increase, their staffing involves more strategic concerns. However, foreign assignments have many differences, and dissatisfaction with the host country is a known cause of expatriate failure. From the point of view of an expatriate candidate, the decision of whether to take an expatriate assignment can be regarded as a FMCDM (fuzzy multiple criteria decision making) problem. This paper describes a fuzzy AHP (fuzzy analytic hierarchy process) to determine the weighting of subjective judgments. Using the Sugeno integral for λ-fuzzy measure, and using the nonadditive fuzzy integral technique to evaluate the synthetic utility values of the alternatives and the fuzzy weights, then the best host country alternative can be derived with the grey relation model. The authors further combine the grey relation model based on the concepts of TOPSIS (technique for order preference by similarity to ideal solution) to evaluate and select the best alternative. A real case of expatriate assignment decision-making was used to demonstrate that the grey relation model combined with the ideas of TOPSIS results in a satisfactory and effective evaluation.

Evaluating sustainable fishing development strategies using fuzzy MCDM approach

Abstract In actual environmental investment for industry, the stakeholders are often required to evaluate the investment strategies according to their own subjective preferences in terms of numerical values from various criteria, such as economic effectiveness, technique feasibility and environmental regulation. Thus, this situation can be regarded as a fuzzy multiple criteria decision-making (MCDM) problem, so the fuzziness and uncertainty of subjective perception should be considered. This paper proposes an alternative approach, the non-additive fuzzy integral, to cope with evaluation of fuzzy MCDM problems particularly while there is dependence among considered criteria. To illustrate the proposed procedure, the sustainable development strategy for aquatic product processors in Taiwan is investigated. In this paper we employ triangular fuzzy numbers to represent the decision makers’ subjective preferences on the considered criteria, as well as for the criteria measurements to evaluate a sustainable development planning case for industry. Firstly, in this study we employ factor analysis to extract four independent common factors from those criteria. Secondly, we construct the evaluation frame using AHP composed of the above four common factors with twelve evaluated criteria, and then derive the relative weights with respect to considered criteria. Thirdly, the synthetic utility value corresponding to each sustainable development strategy is aggregated by the fuzzy weights with fuzzy performance values, and the best investment strategies can then be decided. Through this study, we successfully demonstrate that the non-additive fuzzy integral is an effective evaluation and appears to be more appropriate than the traditional simple additive weighted method, especially when the criteria are dependent.

Fuzzy MCDM based on the concept of α‐cut

AbstractIn a fuzzy multiple criteria decision‐making (MCDM) problem, with a hierarchical structure of more than two levels and involving multiple decision‐makers (DMs), to find the exact membership functions of the final aggregation ratings of all feasible alternatives is almost impossible. Thus, ranking methods based on exact membership functions cannot be utilized to rank the feasible alternatives and complete the optimal selection. To resolve the above‐mentioned complexity and to incorporate assessments of all DMs' viewpoints, in this paper a fuzzy MCDM method with multiple DMs, based on the concepts of fuzzy set theory and α‐cut, is developed. This method incorporates a number of perspectives on how to approach the fuzzy MCDM problem with multiple DMs, as follows: (1) combining quantitative and qualitative criteria as well as negative and positive ones; (2) using the generalized means to develop the aggregation method of multiple DMs' opinions; (3) incorporating the risk attitude index β to convey the total risk attitude of all DMs by using the estimation data obtained at the data input stage; (4) employing the algebraic operations of fuzzy numbers based on the concept of α‐cut to calculate the final aggregation ratings and develop a matching ranking method for proposed fuzzy MCDM method with multiple DMs. Furthermore, we use this method to survey the site selection for free port zone (FPZ) in Taiwan as an empirical study to demonstrate the proposed fuzzy MCDM algorithm. The result of this empirical investigation shows that the port of Kaohsiung, the largest international port of Taiwan as well as the sixth container port in the world in 2004, is optimal for the Taiwan government in enacting the plan of FPZ. Copyright © 2005 John Wiley & Sons, Ltd.