Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: Genetic and Evolutionary Computation Conference, GECCO 2019; Prague; Prague
Год издания: 2019
Ключевые слова: metaheuristic, multi-objective optimization, performance improvement, Restart operator
Аннотация: Incorporating a restart operator into a multi-objective evolutionary algorithm (MOEA) yields its performance improvement. Restarting an algorithm aims at preventing stagnation and reaching solutions uniformly distributed along the whole Pareto front. The presented experimental results for two MOEAs with the restart operator demonstrate vast potential of this metaheuristic. The use of the restart operator is limited by the necessity to adjust its key parameters for the problem solved.
Издание
Журнал: GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion
Номера страниц: 197-198
Персоны
- Brester C. (Reshetnev Siberian State University of Science and Technology)
- Ryzhikov I. (Reshetnev Siberian State University of Science and Technology)
- Kolehmainen M. (University of Eastern Finland)
- Semenkin E. (Reshetnev Siberian State University of Science and Technology)
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