Adaptive, convergent, and diversified archiving strategy for multiobjective evolutionary algorithms
It is crucial to obtain automatically and efficiently a well-distributed set of Pareto optimal solutions in multiobjective evolutionary algorithms (MOEAs). Many studies have proposed different evolutionary algorithms that can progress toward the Pareto front with a widely spread distribution of solutions. However, most theoretically, convergent MOEAs necessitate certain prior knowledge about the Pareto front in order to efficiently maintain widespread solutions. In this paper, we propose, based...[Show more]
|Collections||ANU Research Publications|
|Source:||Expert Systems with Applications|
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