Romanian Journal of Information Technology and Automatic Control / Vol. 25, No. 2, 2015

Multi-objective Optimization Problems Solving based on Evolutionary Algorithm

Iulia Cristina RĂDULESCU

Abstract:

In this article we analyze several approaches for solving multi-objective optimization problems, focusing on the approaches based on evolutionary algorithms. We present a classification of optimization techniques in enumerative, deterministic and stochastic. From the stochastic optimization techniques are detailed Evolutionary Algorithms - EA. These algorithms are successfully used for solving multi-objective optimization. We present the basic concepts used in evolutionary algorithms and an overview of several evolutionary algorithms for solving multi-objective optimization problems. Finally, we solve four multi-objective optimization problems using a well-known evolutionary algorithm called the Non-Dominated Sorting Genetic Algorithms - NSGA-II. The Matlab program, that implements the algorithm NSGA-II, computes the Pareto frontier of the four multi-objective optimization problems considered.

Keywords:
Multi-objective optimization, Evolutionary Algorithms, Non-Dominated Sorting Genetic Algorithms, Pareto frontier

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CITE THIS PAPER AS:
Iulia Cristina RĂDULESCU, "Multi-objective Optimization Problems Solving based on Evolutionary Algorithm", Romanian Journal of Information Technology and Automatic Control, ISSN 1220-1758, vol. 25(2), pp. 39-48, 2015.