Presenting an Optimal Model for Determining the Potential Areas of Industrial Development in Alborz Province

Authors

  • Alireza Gharagozlou Department of Remote Sensing and GIS, Graduate School of the Environment and Energy, Science and Research Branch, IAU, Tehran, Iran
  • Dariush Jaras Department of Environment and PhD of Environmental Assessment
  • Seyed Masoud Monavari Department of Environmental Science, Faculty of Environment and Energy, Science and Research Branch, Islamic Azad University, Tehran, Iran
Abstract:

In this study, three criteria and 10 sub-criteria and 18 indicators based on the ecological, economic and social characteristics of the Alborz province, while reviewing the internal and external resources, and using 30 expert opinions were sought in order to reach a collective consensus. Also to measure their weight, the FAHP fuzzy hierarchy process was used. Then, using weighted linear combination and geographic information system, the fuzzy desirability map of desirable arenas and their area were determined for industrial development of the province. Considering the highest accuracy and overlapping error of each of the models separately provides the best field for industrial development in the province. The results of this study shows that the integration of colonial competition and genetics meta-evolutionary algorithms for optimizing, due to the multiplicity of repetitions to achieve an optimal goal, while considering uncertainty, to provide an optimal model for locating potential and prone areas and prone to industrial development is very useful and it is possible to use it and taking into account the indigenous criteria of each province of the country, to prepare and use the optimal model of industrial development of each province of the country for decision making. The obtained results show that more than 66,000 hectares of research area has capability are based on the optimal compilation model presented for industrial development.

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Journal title

volume 2  issue 4

pages  297- 324

publication date 2018-11-01

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