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Simultaneous Location-Allocation of multiple Facilities using Multi-objective Evolutionary Algorithm based on Decomposition
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Sara Beheshtifar *   |
| Tabriz University |
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Abstract: (1751 Views) |
| Choosing the proper location for service centers can play an important role in reducing travel costs for users, desirable use of the land, and regulation of interactions among different facilities. When Location-Allocation (L.A.) problem of any new service centers is solved for multiple facilities independently, only the effects of existing land uses are taken into consideration , while the establishment of one facility, due to its impact on the surrounding space, may cause limitations for the establishment of other required facilities. By locating all the required centers simultaneously, better results can be obtained for the arrangement of the centers in an area. The main objective of this study is to solve the L.A. problem for several service centers with similar or dissimilar services in GIS environment simultaneously. For this purpose, the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) algorithm has been used to optimize the three objective functions including minimizing travel costs, maximizing the suitability of selected sites, and maximizing the compatibility among the new service centers. The results showed that by using this method, acceptable solutions for the arrangement of different service centers in the study area have been obtained according to the defined objectives. The comparison of the results with Non-Dominated Sorting Genetic Algorithm II (NSGA_II), as one of the most common optimization algorithms, based on various criteria, showed that MOEA/D method has performed well in finding optimized answers so that none of the solutions of this method were dominated by the solutions of the NSGA_II, while the reverse was not true. Besides, from the point of view of the closeness of the answers to the ideal point, MOEA/D has generated better solutions (0.16) and the covered time has been 25% of NSGA_ II method. |
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| Keywords: Location-Allocation, GIS, Multi-objective optimization, MOEA/D, P-median model. |
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Full-Text [PDF 1682 kb]
(610 Downloads)
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Type of Study: Research |
Subject:
GIS
Received: 2021/04/5 | Accepted: 2021/07/19 | Published: 2021/10/22
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