{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,9,6]],"date-time":"2022-09-06T01:11:23Z","timestamp":1662426683387},"reference-count":15,"publisher":"IGI Global","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,4]]},"abstract":"<jats:p>The authors propose a computing approach for solving a multiobjective problem in the telecommunication network field, suggested by an Algerian industrial company. The principal goal is in developing a palliative solution to overcome some generated problems existing in the current management system. A mathematical operational model has been established. The exact algorithms that solve multiobjective optimization problems are not appropriate for large scale problems. However, the application of metaheuristics approach leads perfectly to approximate the Pareto optimal set. In this paper, the authors apply a well-known multiobjective evolutionary algorithm, the Non-dominated Sorting Genetic Algorithm (NSGA-II), compare the obtained results with those generated by the Strength Pareto Evolutionary Algorithm-II (SPEA2) and propose a way to help the decision maker, who is often confronted with the choice of a final solution, to make his preferences afterward using a utility function based on a Choquet integral measure. Finally, numerical experiments are presented to validate the approach.<\/jats:p>","DOI":"10.4018\/ijamc.2020040103","type":"journal-article","created":{"date-parts":[[2020,1,17]],"date-time":"2020-01-17T18:28:57Z","timestamp":1579285737000},"page":"56-76","source":"Crossref","is-referenced-by-count":1,"title":["Evolutionary Metaheuristics to Solve Multiobjective Assignment Problem in Telecommunication Network"],"prefix":"10.4018","volume":"11","author":[{"given":"Benkanoun","family":"Yazid","sequence":"first","affiliation":[{"name":"DGRSDT, USTHB, AMCD-RO Laboratory, BP32 El-Alia, Bab Ezzouar, Algiers, Algeria"}]},{"given":"Bouroubi","family":"Sadek","sequence":"additional","affiliation":[{"name":"DGRSDT, USTHB, L'IFORCE Laboratory, BP32 El-Alia, Bab Ezzouar, Algiers, Algeria"}]},{"given":"Chaabane","family":"Djamal","sequence":"additional","affiliation":[{"name":"DGRSDT, USTHB, AMCD-RO Laboratory, BP32 El-Alia, Bab Ezzouar, Algiers, Algeria"}]}],"member":"2432","reference":[{"key":"IJAMC.2020040103-0","doi-asserted-by":"publisher","DOI":"10.5802\/aif.53"},{"key":"IJAMC.2020040103-1","doi-asserted-by":"publisher","DOI":"10.1109\/4235.996017"},{"key":"IJAMC.2020040103-2","doi-asserted-by":"publisher","DOI":"10.1007\/BF01580453"},{"key":"IJAMC.2020040103-3","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-009-0655-8"},{"key":"IJAMC.2020040103-4","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1007\/978-1-4939-3094-4_14","article-title":"Fuzzy measures and integrals in MCDA","author":"M.Grabisch","year":"2016","journal-title":"Multiple Criteria Decision Analysis"},{"key":"IJAMC.2020040103-5","article-title":"Minimum variance capacity identification","author":"I.Kojadinovic","year":"2006","journal-title":"European Journal of Operational Research"},{"key":"IJAMC.2020040103-6","doi-asserted-by":"publisher","DOI":"10.1090\/S0002-9939-1956-0078686-7"},{"key":"IJAMC.2020040103-7","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2013.04.003"},{"key":"IJAMC.2020040103-8","doi-asserted-by":"publisher","DOI":"10.1016\/S0377-2217(99)00182-4"},{"key":"IJAMC.2020040103-9","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2000.870312"},{"key":"IJAMC.2020040103-10","unstructured":"Mori, T., & Murofushi, T. (1989). An analysis of evaluation model using fuzzy measure and the Choquet integral. In Proceedings of the 5th Fuzzy System Symposium, Kobe, Japan (pp. 207-212). Academic Press. (in Japanese)"},{"key":"IJAMC.2020040103-11","unstructured":"Schott, J. R. (1995). Fault tolerant design using single and multicriteria genetic algorithm optimization [Masters thesis]. Department of Aeronautics and Astronautics, Massachusetts Institute of Technology."},{"key":"IJAMC.2020040103-12","article-title":"Some considerations about computational complexity for multiobjective combinatorial problms","author":"P.Serafini","year":"1986","journal-title":"Recent advances and historical development of vector"},{"key":"IJAMC.2020040103-13","doi-asserted-by":"publisher","DOI":"10.1002\/9780470496916"},{"key":"IJAMC.2020040103-14","unstructured":"Zitzler, E., Laumanns, M., & Thiele, L. (2001). SPEA2: Improving the strength Pareto evolutionary algorithm for multiobjective optimization. In K. C. Giannakoglou, D. T. Tsahalis, J. Priaux et al. (Eds.), Evolutionary Methods for Design Optimization and Control with Applications to Industrial Problems, Athens, Greece (pp. 95\u2013100). Academic Press."}],"container-title":["International Journal of Applied Metaheuristic Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=247057","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T12:15:10Z","timestamp":1651839310000},"score":1,"resource":{"primary":{"URL":"http:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJAMC.2020040103"}},"subtitle":["Multiobjective Assignment Problem"],"short-title":[],"issued":{"date-parts":[[2020,4]]},"references-count":15,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.4018\/ijamc.2020040103","relation":{},"ISSN":["1947-8283","1947-8291"],"issn-type":[{"value":"1947-8283","type":"print"},{"value":"1947-8291","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4]]}}}