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Solving Multi-Objective Optimization Problems by a Bi-Objective Evolutionary Algorithm

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1 Author(s)
Yu-Ping Wang ; School of Computer Science and Technology, Xidian University, Xi'an, 710071, China. E-MAIL:

In this paper a novel model for multiobjective optimization problem is proposed first, in which the multiobjective optimization problem is transformed into a bi-objective optimization problem. In this bi-objective problem one objective is responsible for optimizing the quality of the solutions, and the other is to improve the distribution of the obtained nondominated solution set. Then a new crossover operator and selection scheme are designed. Based on these, a specific-designed evolutionary algorithm is presented. The simulations on five widely used benchmark problems are made and the results indicate that the proposed algorithm is efficient and outperforms the compared algorithms.

Published in:

2007 International Conference on Machine Learning and Cybernetics  (Volume:2 )

Date of Conference:

19-22 Aug. 2007