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Multi Objective Optimization with a New Evolutionary Algorithm
Stockholm University, Faculty of Science, Department of Physical Geography.
Number of Authors: 22018 (English)In: Water resources management, ISSN 0920-4741, E-ISSN 1573-1650, Vol. 32, no 12, p. 4013-4030Article in journal (Refereed) Published
Abstract [en]

Various objectives are mainly met through decision making in real world. Achieving desirable condition for all objectives simultaneously is a necessity for conflicting objectives. This concept is called multi objective optimization widely used nowadays. In this study, a new algorithm, comprehensive evolutionary algorithm (CEA), is developed based on general concepts of evolutionary algorithms that can be applied for single or multi objective problems with a fixed structure. CEA is validated through solving several mathematical multi objective problems and the obtained results are compared with the results of the non-dominated sorting genetic algorithm II (NSGA-II). Also, CEA is applied for solving a reservoir operation management problem. Comparisons show that CEA has a desirable performance in multi objective problems. The decision space is accurately assessed by CEA in considered problems and the obtained solutions' set has a great extent in the objective space of each problem. Also, CEA obtains more number of solutions on the Pareto than NSGA-II for each considered problem. Although the total run time of CEA is longer than NSGA-II, solution set obtained by CEA is about 32, 4.4 and 1.6% closer to the optimum results in comparison with NSGA-II in the first, second and third mathematical problem, respectively. It shows the high reliability of CEA's results in solving multi objective problems.

Place, publisher, year, edition, pages
2018. Vol. 32, no 12, p. 4013-4030
Keywords [en]
Evolutionary algorithm, Multi colony, Multi objective, Optimization, Pareto
National Category
Civil Engineering Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:su:diva-158887DOI: 10.1007/s11269-018-2034-1ISI: 000440830200013OAI: oai:DiVA.org:su-158887DiVA, id: diva2:1240783
Available from: 2018-08-22 Created: 2018-08-22 Last updated: 2018-08-22Bibliographically approved

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Seifollahi-Aghmiuni, Samaneh
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