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On a restartmetaheuristic forreal-valuedmulti-objectiveevolutionaryalgorithms : доклад,тезисы доклада Brester C.Ryzhikov I.Kolehmainen M.2019 год

On a restart metaheuristic for real-valued multi-objective evolutionary algorithms : доклад, тезисы доклада
доклад, тезисы доклада, статья из сборника материалов конференций

Дополнительные ссылки: eLibrary · Источник статьи
База данных: Каталог библиотеки СФУ
Библиографическое описание: On a restart metaheuristic for real-valued multi-objective evolutionary algorithms : доклад, тезисы доклада / C. Brester [et al.]. - Текст : непосредственный // GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion / 2019 Genetic and Evolutionary Computation Conference, GECCO 2019 (2019 ; 13.07 - 17.07 ; Prague). - 2019. - P. 197-198.
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.
Год издания: 2019
Авторы: Brester C. , Ryzhikov I. , Kolehmainen M. , Semenkin E.
Источник: GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion
Номера страниц: 197-198
Держатель оригинала документа: Reshetnev Siberian State University of Science and Technology, University of Eastern Finland
Мероприятие: Genetic and Evolutionary Computation Conference, GECCO 2019 (Prague, 2019 ; 13.07 - 17.07)
Количество экземпляров:
Твёрдая копия издания отсутствует в фонде библиотеки

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