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On the hybridization of SMS-EMOA and local search for continuous multiobjective optimization
2009
Proceedings of the 11th Annual conference on Genetic and evolutionary computation - GECCO '09
In the recent past, hybrid metaheuristics became famous as successful optimization methods. The motivation for the hybridization is a notion of combining the best of two worlds: evolutionary black box optimization and local search. Successful hybridizations in large combinatorial solution spaces motivate to transfer the idea of combining the two worlds to continuous domains as well. The question arises: Can local search also improve the convergence to the Pareto front in continuous
doi:10.1145/1569901.1569985
dblp:conf/gecco/KochKRB09
fatcat:x3mrs3vpnbfxjogbao4ozp4p4y