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Issue title: Selected papers from the 9th International Multi-Conference on Engineering and Technology Innovation 2019 (IMETI2019)
Guest editors: Wen-Hsiang Hsieh
Article type: Research Article
Authors: Wang, Sheng-Chuana; b; * | Chen, Ta-Chengc; d
Affiliations: [a] Department of Finance, Asia University, Taichng, Taiwan | [b] Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan | [c] Department of M-Commerce and Multimedia Applications, Asia University, Taichung, Taiwan | [d] Department of Information Management, National Formosa University, Yunlin, Taiwan
Correspondence: [*] Corresponding author. Sheng-Chuan Wang, E-mail: [email protected].
Abstract: Multi-objective competitive location problem with cooperative coverage for distance-based attractiveness is introduced in this paper. The potential facilities compete to be selected to serve all demand points which are determined by maximizing total collective attractiveness of all demand points from assigned facilities and minimizing the fixed and distance costs between all demand points and selected facilities. Facility attractiveness is represented as a coverage of the facility with full, partial and none coverage corresponding to maximum full and partial coverage radii. Cooperative coverage, which the demand point is covered by at least one facility, is also considered. The problem is formulated as a multi-objective optimization model and solution procedure based on elitist non-dominated sorting genetic algorithms (NSGA-II) is developed. Experimental example demonstrates the best non-dominated solution sets obtained by developed solution procedure. Contributions of this paper include introducing competitive location problem with facility attractiveness as a distance-based coverage of the facility, re-categorizing facility coverage classification and developing solution procedure base upon NSGA-II.
Keywords: Competitive location problem, facility attractiveness, distance-based coverage, cooperative coverage, elitist non-dominated sorting genetic algorithms (NSGA-II)
DOI: 10.3233/JIFS-189592
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7723-7734, 2021
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