An advanced decision-making model for evaluating manufacturing plant locations using fuzzy inference system

被引:15
作者
Paul, Sanjoy Kumar [1 ]
Chowdhury, Priyabrata [2 ]
Ahsan, Kamrul [2 ]
Ali, Syed Mithun [3 ]
Kabir, Golam [4 ]
机构
[1] Univ Technol Sydney, UTS Business Sch, Sydney, NSW, Australia
[2] RMIT Univ, Sch Accounting Informat Syst & Supply Chain, Melbourne, Vic, Australia
[3] Bangladesh Univ Engn & Technol, Dept Ind & Prod Engn, Dhaka, Bangladesh
[4] Univ Regina, Fac Engn & Appl Sci, Ind Syst Engn, Regina, SK, Canada
关键词
Manufacturing plant location; Intelligent decision-making; Fuzzy inference system; Multi-criteria decision-making; ANALYTIC HIERARCHY PROCESS; FACILITY LOCATION; SUPPORT-SYSTEM; SELECTION; MULTICRITERIA; ENVIRONMENT; DESIGN; TOPSIS; SITE; AHP;
D O I
10.1016/j.eswa.2021.116378
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Locating a manufacturing plant is a complex multi-criteria decision-making problem as it involves many tangible and intangible criteria. This paper contributes to the existing theory by integrating a qualitative Delphi and a quantitative fuzzy inference system (FIS) for developing an advanced and intelligent decision-making framework for evaluating manufacturing plant locations. The Delphi method is used to identify the most significant manufacturing plant location selection criteria. The identified major criteria are used to develop an advanced FIS framework to evaluate potential manufacturing plant locations. A real-life case is presented to demonstrate the applicability of the developed decision-making framework. This paper contributes to the literature by developing an advanced decision-making framework for evaluating manufacturing plant locations and by integrating qualitative Delphi and quantitative FIS, which can help industrial managers locate their manufacturing plant locations intelligently and accurately.
引用
收藏
页数:15
相关论文
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