Evolutionary algorithm portfolios based on information sharing
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Abstract
A general framework for combining multiple evolutionary algorithms EAP_IS is proposed. Each of the constituent algorithms in this framework has its own population to maintain its characteristic and the continuity of the evolution process. EAP_IS runs each constituent algorithm with a part of the given time budget and encourages information sharing among the constituent algorithms. The effectiveness of EAP_IS has been verified by investigating 26 instantiations of it on 25 benchmark functions, and further comparisons of EAP_IS with other combinatorial frameworks have been conducted. Experimental results show that the proposed framework can improve the performance of constituent algorithms effectively.
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