A ε-indicator-based shuffled frog leaping algorithm for many-objective optimization problems |
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Authors: | WANG Na SU Yuchao CHEN Xiaohong LI Xia LIU Dui |
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Institution: | College of Electronics and Information Engineering;Guangdong Key Laboratory of Intelligent Information Processing |
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Abstract: | Many-objective optimization problems take challenges to multi-objective evolutionary algorithms. A number of non-dominated solutions in population cause a difficult selection towards the Pareto front. To tackle this issue, a series of indicatorbased multi-objective evolutionary algorithms(MOEAs) have been proposed to guide the evolution progress and shown promising performance. This paper proposes an indicator-based manyobjective evolutionary algorithm called ε-indicator-based shuffled frog leaping algorithm(ε-MaOSFLA), which adopts the shuffled frog leaping algorithm as an evolutionary strategy and a simple and effective ε-indicator as a fitness assignment scheme to press the population towards the Pareto front. Compared with four stateof-the-art MOEAs on several standard test problems with up to 50 objectives, the experimental results show that ε-MaOSFLA outperforms the competitors. |
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Keywords: | evolutionary algorithm many-objective optimization shuffled frog leaping algorithm(SFLA) ε-indicator |
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