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Article type: Research Article
Authors: Jarernsuk, Saran | Phruksaphanrat, Busaba; *
Affiliations: Thammasat University Research Unit in Industrial Statistics and Operational Research, Industrial Engineering Department, Faculty of Engineering, Thammasat School of Engineering, Thammasat University, Pathumthani, Thailand
Correspondence: [*] Corresponding author. Busaba Phruksaphanrat, Thammasat University Research Unit in Industrial Statistics and Operational Research, Industrial Engineering Department, Faculty of Engineering, Thammasat School of Engineering, Thammasat University, Pathumthani, 12121, Thailand. E-mail: lbusaba@engr.tu.ac.th.
Abstract: Fuzzy multiple objective linear programming (FMOLP) approaches have been used to be solved many applications of multi-objective decision-making (MODM) problems. Several methods have been proposed including max-min approaches, preemptive approaches, and weighted approaches. However, they have some limitations in use; some may not be able to obtain efficient solutions or can give only a few solutions. Some methods need to be solved in two steps or specify the target level, which may be difficult for decision-makers (DMs). In this research, a new single-phase interactive fuzzy programming approach with priority control that can find several efficient solutions is proposed. It is not necessary to specify the target value for each objective and it can solve with only one step for each solution. The DM can easily select the appropriate solutions from a set of efficient solutions. This method is different from existing single-phase approaches by controlling the satisfaction level of the last priority instead of using weight additive. Simple examples and a practical example of a perishable product supply chain network were tested to show the effectiveness of the proposed model. The performance of the proposed method was also compared with existing methods to verify and validate the model.
Keywords: Fuzzy programming, multiple objective decision making, fuzzy-efficient solution, priority, perishable products supply chain network
DOI: 10.3233/JIFS-220367
Journal: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7779-7792, 2022
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