A new preference voting method for sustainable location planning using geographic information system and data envelopment analysis

被引:32
作者
Izadikhah, Mohammad [1 ]
Saen, Reza Farzipoor [2 ]
机构
[1] Islamic Azad Univ, Arak Branch, Coll Sci, Dept Math, POB 38135-567, Arak, Iran
[2] Islamic Azad Univ, Karaj Branch, Fac Management & Accounting, Dept Ind Management, POB 31485-313, Karaj, Iran
关键词
Sustainable location planning; Geographic information system (GIS); Data envelopment analysis (DEA); Voting system; Strong complementary slackness; SUPPLY CHAIN MANAGEMENT; BOTTOM-LINE APPROACH; ANALYSIS MODEL; RANKING MODEL; SELECTION; GREEN; DEA; CRITERIA; NETWORK; EFFICIENCY;
D O I
10.1016/j.jclepro.2016.08.021
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Supply chain operations with sustainability considerations have become an increasingly important issue in recent years and location planning for sustainable development plays an important role in guiding future of local, regional and national systems. Geographic information system is a technology for making better decisions about location. To solve location planning problem, in this paper, a new preference aggregation algorithm using complementary slackness condition and discriminant analysis is developed. Applying a voting system for solving sustainable location planning problem is new and cannot be found in literature. Using geographic information system and factor analysis, a multiple attribute decision making problem is developed. In this paper, multiple attribute decision making problems are solved by our proposed method for ranking a voting system and also the sustainable location is obtained. A case study demonstrates efficiency of proposed method. For this purpose, the proposed method is used to determine the most appropriate locations for constructing agro-industries in Markazi province. In our real application, ten main criteria using obtained variances and eigen values are recognized. Seven locations are selected and ranked. Results show that Komain is the best location for constructing agroindustry and Komijan is the worst location. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1347 / 1367
页数:21
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