Multi-Objective Optimization Model for the Allocation of Water Resources in Arid Regions Based on the Maximization of Socioeconomic Efficiency
| العنوان: | Multi-Objective Optimization Model for the Allocation of Water Resources in Arid Regions Based on the Maximization of Socioeconomic Efficiency |
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| المؤلفون: | M. Habibi Davijani, S. R. Hashemi, Mohammad Ebrahim Banihabib, A. Nadjafzadeh Anvar |
| المصدر: | Water Resources Management. 30:927-946 |
| بيانات النشر: | Springer Science and Business Media LLC, 2016. |
| سنة النشر: | 2016 |
| مصطلحات موضوعية: | business.industry, 0208 environmental biotechnology, Particle swarm optimization, 02 engineering and technology, Production function, Maximization, 010501 environmental sciences, Environmental economics, 01 natural sciences, Multi-objective optimization, Profit (economics), 020801 environmental engineering, Water resources, Demand curve, Agriculture, Economics, Water resource management, business, 0105 earth and related environmental sciences, Water Science and Technology, Civil and Structural Engineering |
| الوصف: | The escalating world population has led to a drastic increase in water demand in the municipal and drinking water, agriculture and industry sectors. This situation necessitates application of effective measures for the optimal and efficient management of water resources. With this respect, a two-objective socioeconomic model (aimed at job creation) has been presented in this study for the optimum allocation of water resources to industry, agriculture and municipal water sectors. In the agriculture sector, the production function of each product has been determined and then, based on the production functions, areas under cultivation, product yield and the income obtained from each product, the combined objective function has been specified. In the industry sector, since water demand is a function of the amount of produced products, price of supplied water and the price of other supplies, the demand function of this sector was determined regionally. Also, considering the existing necessity in meeting the municipal water requirement, the total amount of water needed by this sector was fully allocated. Then by using two meta-heuristic algorithms, i.e. genetic algorithm (GA) and particle swarm optimization (PSO), the objective functions were maximized and the water resources were optimally allocated between agriculture and industry sectors and the results were compared. Ultimately, comparing the results gained by PSO and GA algorithms, PSO with an economic and profit growth of 54 % and a 13 % rise in employment relative to the base condition, turned out to be more efficient in this application. |
| تدمد: | 1573-1650 0920-4741 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::b0cb402ac0253f3cb4b73869cddc32d8 https://doi.org/10.1007/s11269-015-1200-y |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi...........b0cb402ac0253f3cb4b73869cddc32d8 |
| قاعدة البيانات: | OpenAIRE |
Find this article in full text from Springer Verlag. | تدمد: | 15731650 09204741 |
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