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

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2022年 / 191卷

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

页数：15

共 83 条

[71] Cross-border e-commerce commodity risk assessment using text mining and fuzzy rule-based reasoning [J].

Song, Bo ;

Yan, Wei ;

Zhang, Tianjiao .

ADVANCED ENGINEERING INFORMATICS, 2019, 40 :69-80

[72]

Sung W. C., 2001, J. Healthc. Manag, V2, P11

[73]

Tahriri Farzad, 2014, Journal of Industrial Engineering International, V10, DOI 10.1007/s40092-014-0066-6

[74] A multi-objective mixed robust possibilistic flexible programming approach for sustainable seaport-dry port network design under an uncertain environment [J].

Tsao, Yu-Chung ;

Vo-Van Thanh .

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2019, 124 :13-39

[75] Analytic network process approach for locating undesirable facilities:: An example from Istanbul, Turkey [J].

Tuzkaya, Guelfem ;

Onut, Semih ;

Tuzkaya, Umut R. ;

Gulsun, Bahadir .

JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2008, 88 (04) :970-983

[76]

Tzeng GwoHshiung Tzeng GwoHshiung, 2002, International Journal of Hospitality Management, V21, P171, DOI 10.1016/S0278-4319(02)00005-1

[77] An advanced fuzzy Bayesian-based FMEA approach for assessing maritime supply chain risks [J].

Wan, Chengpeng ;

Yan, Xinping ;

Zhang, Di ;

Qu, Zhuohua ;

Yang, Zaili .

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2019, 125 :222-240

[78] Multiobjective Multiple Neighborhood Search Algorithms for Multiobjective Fleet Size and Mix Location-Routing Problem With Time Windows [J].

Wang, Jiahai ;

Yuan, Liangsheng ;

Zhang, Zizhen ;

Gao, Shangce ;

Sun, Yuyan ;

Zhou, Yalan .

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (04) :2284-2298

[79] Knowledge-driven intelligent quality problem-solving system in the automotive industry [J].

Xu, Zhaoguang ;

Dang, Yanzhong ;

Munro, Peter .

ADVANCED ENGINEERING INFORMATICS, 2018, 38 :441-457

[80] Multiple-attribute decision making methods for plant layout design problem [J].

Yang, Taho ;

Hung, Chih-Ching .

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2007, 23 (01) :126-137

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