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

• Published in: Journal of cleaner production Vol. 137; pp. 1347 - 1367
• Main Authors: Izadikhah, Mohammad, Saen, Reza Farzipoor
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 20.11.2016
• Subjects: Data envelopment analysis (DEA); Geographic information system (GIS); Strong complementary slackness; Sustainable location planning; Voting system; Data envelopment analysis (DEA); Geographic information system (GIS); Strong complementary slackness; Sustainable location planning; Voting system
• ISSN: 0959-6526; 1879-1786
• DOI: 10.1016/j.jclepro.2016.08.021

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 agro-industry and Komijan is the worst location. •Our approach ranks all candidates.•For the first time, we apply our proposed voting method for solving MADM problem.•We determine appropriate locations for constructing sustainable agro-industries.