Multiple criteria decision making based on bipolar fuzzy sets application to fuzzy TOPSIS

In today’s highly turbulent and competitive environment, the success of the organization depends on the performance of its suppliers. However, supplier selection problems are complex as they involve a large number of criteria and, frequently, some of the criteria cannot be evaluated precisely. Moreover, fluctuations of supplier performances and unknown information always exist in real-world decision-making. It is a complex multiple-criteria decision-making (MCDM) problem as it involves a trade-off among various criteria with vagueness and imprecision and also involves a group of experts with diverse opinion. Therefore, to make more practical decisions, this paper is intended to propose an integrated technique for order preference by similarity to ideal solution (TOPSIS) in fuzzy environment with multi-choice goal programming (MCGP) to handle the supplier assessment and order allocation for a battery manufacturing organization. Using linguistic variables, the decision-makers assess the rating of suppliers as well as the importance of various factors. Linguistic variables are expressed in trapezoidal fuzzy numbers (TrFN). Fuzzy-TOPSIS method is proposed to obtain the rank of suppliers and MCGP method is used to allocate suitable orders to the selected suppliers. A case study is implemented to find the applicability and validity of the proposed model. Finally, sensitivity analysis is performed to observe the effect of weights of criteria on supplier evaluation problem.

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Multiple Criteria Decision Making Based on Probabilistic Interval-Valued Hesitant Fuzzy Sets by Using LP Methodology

Discrete Dynamics in Nature and Society ◽

10.1155/2019/1527612 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12 ◽

Cited By ~ 4

Author(s):

M. Sarwar Sindhu ◽

Tabasam Rashid ◽

Agha Kashif ◽

Juan Luis García Guirao

Keyword(s):

Decision Making ◽

Fuzzy Sets ◽

Real Life ◽

Multiple Criteria Decision Making ◽

Multiple Criteria ◽

Decision Makers ◽

Occurrence Probability ◽

Hesitant Fuzzy Sets ◽

Life Problems ◽

Interval Valued

Probabilistic interval-valued hesitant fuzzy sets (PIVHFSs) are an extension of interval-valued hesitant fuzzy sets (IVHFSs) in which each hesitant interval value is considered along with its occurrence probability. These assigned probabilities give more details about the level of agreeness or disagreeness. PIVHFSs describe the belonging degrees in the form of interval along with probabilities and thereby provide more information and can help the decision makers (DMs) to obtain precise, rational, and consistent decision consequences than IVHFSs, as the correspondence of unpredictability and inaccuracy broadly presents in real life problems due to which experts are confused to assign the weights to the criteria. In order to cope with this problem, we construct the linear programming (LP) methodology to find the exact values of the weights for the criteria. Furthermore these weights are employed in the aggregation operators of PIVHFSs recently developed. Finally, the LP methodology and the actions are then applied on a certain multiple criteria decision making (MCDM) problem and a comparative analysis is given at the end.

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A prioritized aggregation operator-based approach to multiple criteria decision making using interval-valued intuitionistic fuzzy sets: A comparative perspective

Information Sciences ◽

10.1016/j.ins.2014.05.018 ◽

2014 ◽

Vol 281 ◽

pp. 97-112 ◽

Cited By ~ 46

Author(s):

Ting-Yu Chen

Keyword(s):

Decision Making ◽

Fuzzy Sets ◽

Multiple Criteria Decision Making ◽

Intuitionistic Fuzzy Sets ◽

Aggregation Operator ◽

Multiple Criteria ◽

Comparative Perspective ◽

Intuitionistic Fuzzy ◽

Prioritized Aggregation Operator ◽

Interval Valued

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Multiple criteria decision making based on Hamy mean operators under the environment of spherical fuzzy sets

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-201708 ◽

2021 ◽

pp. 1-26

Author(s):

Muhammad Sarwar Sindhu ◽

Tabasam Rashid ◽

Agha Kashif

Keyword(s):

Decision Making ◽

Fuzzy Sets ◽

Closed Interval ◽

Multiple Criteria Decision Making ◽

Score Function ◽

Vital Role ◽

Multiple Criteria ◽

Uncertain Information ◽

Membership Degree ◽

Picture Fuzzy Sets

Aggregation operators are widely applied to accumulate the vague and uncertain information in these days. Hamy mean (HM) operators play a vital role to accumulate the information. HM operators give us a more general and stretchy approach to develop the connections between the arguments. Spherical fuzzy sets (SpFSs), the further extension of picture fuzzy sets (PcFSs) that handle the data in which square sum of membership degree (MD), non-membership degree (NMD) and neutral degree (ND) always lie between closed interval [0, 1]. In the present article, we modify the HM operators like spherical fuzzy HM (SpFHM) operator and weighted spherical fuzzy HM (WSpFHM) operator to accumulate the spherical fuzzy (SpF) information. Moreover, various properties and some particular cases of SpFHM and the WSpFHM operators are discussed in details. Also, to compare the results obtained from the HM operators a score function is developed. Based on WSpFHM operator and score function, a model for multiple criteria decision-making (MCDM) is established to resolve the MCDM problem. To check the significance and robustness of the result, a comparative analysis and sensitivity analysis is also performed.

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