GIS Based Multi-Criteria Analysis for Industrial Site Selection

被引:151
作者
Rikalovic, Aleksandar [1 ]
Cosic, Ilija [1 ]
Lazarevic, Djordje [1 ]
机构
[1] Univ Novi Sad, Fac Tech Sci, Novi Sad 21000, Serbia
来源
24TH DAAAM INTERNATIONAL SYMPOSIUM ON INTELLIGENT MANUFACTURING AND AUTOMATION, 2013 | 2014年 / 69卷
关键词
industrial site selection; geographic information systems; GIS; multi-criteria decision analysis; MCDA; Decision support system; DSS; ArcGIS; IDRISI; GEOGRAPHICAL INFORMATION-SYSTEMS; DECISION-ANALYSIS;
D O I
10.1016/j.proeng.2014.03.090
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Site selection is one of the basic vital decisions in the start-up process, expansion or relocation of businesses of all kinds. Construction of a new industrial system is a major long-term investment, and in this sense determining the location is critical point on the road to success or failure of industrial system. One of the main objectives in industrial site selection is finding the most appropriate site with desired conditions defined by the selection criteria. Most of the data used by managers and decision makers in industrial site selection are geographical which means that industrial site selection process is spatial decision problem. Such studies are becoming more and more common, due to the availability of the Geographic Information Systems (GIS) with user-friendly interfaces. Geographic information systems (GIS) are powerful tool for spatial analysis which provides functionality to capture, store, query, analyze, display and output geographic information. Geographic Information Systems are used in conjunction with other systems and methods such as systems for decision making (DSS) and the method for multi-criteria decision making (MCDM). Synergistic effect is generated by combining these tools contribute to the efficiency and quality of spatial analysis for industrial site selection. This paper presents a successful solution for spatial decision support in the case of spatial analysis of Vojvodina as a region of interest for industrial site selection. (C) 2014 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:1054 / 1063
页数:10
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