Evaluation of Industrial Development Potential Using a Sustainable Approach Based on VIKOR and ANP Hybrid Methods in a Fuzzy Environment: a Case Study in Azarshahr City, Iran
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Abstract
The strategic advantages of sparsely populated towns near major cities make them suitable for the industrial activities. This study was aimed to identify and rank the industrial estate development environmental factors in order to minimize negative environmental effects. In this study, the criteria for industrial development were first determined; then, the weight of each criterion was obtained through the technique known as Analytical Network Process (ANP). These indices were entered into Geographic Information Systems based on 13 defined layers, then compiled and standardized using the fuzzy method. Afterward, selected options were ranked via the VIKOR technique and the final site for industrial development was determined in a fuzzy GIS. According to the results, the most important industrial estate development suitability criteria assessments were environmental, social, and economic, respectively. The results also showed that the sub-criterion of distance from city was the most important environmental pollution factor. The environmental pollution was considered a sub-criterion of social criteria in this study. Generally, environmental criteria to develop an industrial estate were significantly important and should be duly considered in the development of industrial towns. Additionally, the main cause of environmental problems in industrial towns was their proximity to a city zone. This methodology may provide useful information in the development of industrial settlements and may also reduce environmental pollution.
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https://doi.org/ 10. 1016/j.jclepro.2015.09.051
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https://doi.org/10.1016/j.ijpe.2004.02.006
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22 Zhao R., Govind R. Defuzzification of fuzzy intervals. Fuzzy Set Syst. 1991; Vol.43, pp: 45–55.
23 Grekousis G., Manetos P. Photis YN. Modeling urban evolution using neural networks, fuzzy logic and GIS: The case of the Athens metropolitan area. Cities. 2013; Vol.30, pp: 193-203.
http://dx.doi.org/10.1016/j.cities.2012.03.006
24 Opricovic S., Tzeng G. H. Extended VIKOR method in comparison with outranking methods. Eur. J. Oper. Res. 2007; Vol.178, pp: 514–529.
https://doi.10.1016 /j.ejor .2006.01.020
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https://doi.org/10.1111/1467-8667.00269
26 Ruiz P., Fernández I., Ortiz JJ, Pérez A., Fernández P. The Development of a New Methodology Based on GIS and Fuzzy Logic to Locate Sustainable Industrial Areas, 10th AGILE International Conference on Geographic Information Science 2007 Aalborg University, Denmark.2007.
27 Akkaya G., Turanoğlu B., Öztaş S. An compiled fuzzy AHP and fuzzy MOORA approach to the problem of industrial engineering sector choosing. Expert. Syst. Appl. 2015; Vol.42, pp: 9565–9573.
https://doi.org/10.1016/j.eswa.2015.07.061
28 Alikhani R., Azar A. A hybrid fuzzy satisfying optimization model for sustainable gas resources allocation. J. Clean. Prod. 2015; Vol.107, pp: 353–365.
https://doi.org/ 10.1016/j.jclepro.2015.01.064
2 Ruiz M.C., Romero E., Pérez MA., Fernandez I. Development and application of a multi-criteria spatial decision support system for planning sustainable industrial areas in Northern Spain. Automation in Constr. 2011; Vol. 22, pp: 320–333.
https://doi .10.1016 /j. autcon.2011.09.009
3 Fernandez I., Ruiz M C. Descriptive model and evaluation system to locate sustainable industrial areas. J. Clean. Prod. 2009; Vol.17, pp: 87-100.
https://doi.org/10.016/ j.jclepro.2008.02.011
4 Lorestani B., Yousefi N., Cheraghi M. Phytoextraction and phytostabilization potential of plants grown in the vicinity of heavy metal-contaminated soils: a case study at an industrial town site. Environ. Monit. Assess. 2013; Vol.185, p: 10217-10223. https://doi.org/10.1007/s10661-013-3326-9
5 Stuczynski T., Siebielec G., Korzeniowska-Puculek R. Geographical location and key sensitivity issues of post-industrial regions in Europe. Environ. Monit. Assess. 2009; Vol.151, pp: 77-91. https://doi.org/10.1007/s10661-008-0251-4
6 Omidvari M., Ghandehari M. Urban Environmental Management Performance Assessment by Fuzzy Analytical Hierarchy Processing (FAHP). J. Environ. Accont. Manag. 2014; Vol.2, pp: 31-41. [Persian]
https://doi.10.5890/JEAM.2014.03.003
7 Pilouk S., Koottatep T. Environmental performance indicators as the key for eco-industrial parks in Thailand. J. Clean. Prod. 2017; Vol. 156, pp: 614-623.
https://doi.org /10. 1016/ j.jclepro.2017.04.076
8 Liu Z., Adams M., Raymond P., Yong Geng C., Chen Q., Liu W., Sun L., Yu X. Comprehensive development of industrial symbiosis for the response of greenhouse gases emission mitigation: Challenges and opportunities in China. Energy. Policy. 2017; Vol.102, pp: 88-95.
https://doi.org/10.1016/j.enpol.2016.12.013
9 Parajuli I., Lee H. Study on integration techniques for Environmental Impact Assessment of different media based standard industrial classification: A case study of South Korea, J. Clean. Prod. 2017; Vol.151, pp: 643-651.
https://doi.org/10.1016/j.jclepro.2017.03.012
10 Navaie aznave Z., Omidvari M. Safety Risk assessment in Motor vehicle industries by using William fine and ANP-DEMATEL. ioh. 2017; Vol.14 (1), pp: 57-70.
http://ioh.iums.ac.ir/article-1-1643-fa.html
11 Shahabi S., Salehi A., Seifolahi M. Investigation of the Factors Influencing the success of Rural Industries in Employment Generation (Case Study: Isfahan Province). J. Res. Rural. Plan. 2015; Vol.4, pp: 9-11.
12 Madadi M. Evaluation of location of industrial towns of Chaharmahal and Bakhtiari Province case study: Shahhrekord Industrial town, MS Thesis, University of Tabriz. 2003. [Persian]
13 Ahadnezhad M., Zolfi A., Norouzi Mj. An analysis of the location of land to establish industry using AHP & VIKOR methods (Case study: central section of Aras free zone), Environ. Based Territorial Plann. (AMAYESH). 2013; Vol.7, pp: 63-82. [Persian]
14 Dalir F., Shafiepour Motlagh M., Ashrafi K. Sensitivity analysis of parameters affecting carbon footprint of fossil fuel power plants based on life cycle assessment scenarios. Global J. Environ. Sci. Manage. 2016, Vol.3 (1), pp: 75-88.
https://DOI.10.22034/gjesm.2017.03.01.008
15 Aragonés-Beltrán P., Ferrandoa J., García F., Agullóa A. An Analytic Network Process approach for siting a municipal solid waste plant in the Metropolitan Area of Valencia (Spain). J. Environ. Manage. 2010; Vol.91, pp: 1071-86.
https://doi.org/10 .1016 /j.jenvman.2009.12.007
16 Rikalovic A., Cosic I., Lazarevic D. GIS Based Multi-Criteria Analysis for Industrial Site Selection. Procedia Eng. 2014; Vol. 69, pp: 1054-1063.
https://DOI:10.1016 /j.proeng .2014.03.090
17 Liu H.C., Liu L., Mao L.X. Risk evaluation in failure mode and effects analysis with extended VIKOR under fuzzy environment. Expert. Syst. Appl. 2012; Vol.39, pp: 12926-12934.
https://doi.org/10.1016/j.eswa.2012.05.031
18 Park JM., Park J.Y., Park H.S. A review of the National Eco-Industrial Park Development Program in Korea: progress and achievements in the first phase, 2005–2010. J. Clean. Prod. 2016; Vol.114, pp: 33-44.
https://doi.org/10. 1016/ j.jclepro. 2015.08.115
19 Geng Y., Fujita T., Park HS., Chiu ASF., Huisingh D. Progress on innovative eco-industrial development. J. Clean. Prod. 2016; Vol.114, pp: 1-10.
https://doi.org/ 10. 1016/j.jclepro.2015.09.051
20 Chung SH., Lee AH L., Pearn WL. Analytic network process (ANP) approach for product mix planning in semiconductor fabricator. Int. J. Prod. Econ. 2005; Vol. 96, pp: 15–36.
https://doi.org/10.1016/j.ijpe.2004.02.006
21 Saaty R W. Decision making in complex environment: The analytic hierarchy process (AHP) for decision making and the analytic network process (ANP) for decision making with dependence and feedback. Pittsburgh: Super Decisions. 2003.
22 Zhao R., Govind R. Defuzzification of fuzzy intervals. Fuzzy Set Syst. 1991; Vol.43, pp: 45–55.
23 Grekousis G., Manetos P. Photis YN. Modeling urban evolution using neural networks, fuzzy logic and GIS: The case of the Athens metropolitan area. Cities. 2013; Vol.30, pp: 193-203.
http://dx.doi.org/10.1016/j.cities.2012.03.006
24 Opricovic S., Tzeng G. H. Extended VIKOR method in comparison with outranking methods. Eur. J. Oper. Res. 2007; Vol.178, pp: 514–529.
https://doi.10.1016 /j.ejor .2006.01.020
25 Opricovic S., Tzeng G.H. Multi-criteria planning of post-earthquake sustainable reconstruction. Comp. aided civil and infrastructure. eng. 2002; Vol.17, pp: 211-220.
https://doi.org/10.1111/1467-8667.00269
26 Ruiz P., Fernández I., Ortiz JJ, Pérez A., Fernández P. The Development of a New Methodology Based on GIS and Fuzzy Logic to Locate Sustainable Industrial Areas, 10th AGILE International Conference on Geographic Information Science 2007 Aalborg University, Denmark.2007.
27 Akkaya G., Turanoğlu B., Öztaş S. An compiled fuzzy AHP and fuzzy MOORA approach to the problem of industrial engineering sector choosing. Expert. Syst. Appl. 2015; Vol.42, pp: 9565–9573.
https://doi.org/10.1016/j.eswa.2015.07.061
28 Alikhani R., Azar A. A hybrid fuzzy satisfying optimization model for sustainable gas resources allocation. J. Clean. Prod. 2015; Vol.107, pp: 353–365.
https://doi.org/ 10.1016/j.jclepro.2015.01.064
| Files | ||
| Issue | Vol 11 No 2 (2019) | |
| Section | Original Article(s) | |
| Published | 2019-08-11 | |
| Keywords | ||
| Industrial Development Potential Environmental VIKOR Fuzzy Geographic Information Systems Analytical Network Process | ||
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Omidvari M, Etminanmehr F. Evaluation of Industrial Development Potential Using a Sustainable Approach Based on VIKOR and ANP Hybrid Methods in a Fuzzy Environment: a Case Study in Azarshahr City, Iran. Int J Occup Hyg. 2019;11(2):98-113.
