Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: V International Workshop on Mathematical Models and their Applications 2016; Krasnoyarsk, Russia; Krasnoyarsk, Russia
Год издания: 2017
Ключевые слова: bionics, evolutionary algorithms, heuristic algorithms, heuristic methods, learning algorithms, Particle swarm optimization (PSO), Cooperative works, Cuckoo search algorithms, Firefly Algorithms, Fish school searches, Meta-heuristic approach, Number of components, Real-parameter optimization, Related algorithms, optimization
Аннотация: Previously, a meta-heuristic approach, called Co-Operation of Biology-Related Algorithms or COBRA, for solving real-parameter optimization problems was introduced and described. COBRA's basic idea consists of a cooperative work of five well-known bionic algorithms such as Particle Swarm Optimization, the Wolf Pack Search, the Firefly Algorithm, the Cuckoo Search Algorithm and the Bat Algorithm, which were chosen due to the similarity of their schemes. The performance of this meta-heuristic was evaluated on a set of test functions and its workability was demonstrated. Thus it was established that the idea of the algorithms' cooperative work is useful. However, it is unclear which bionic algorithms should be included in this cooperation and how many of them. Therefore, the five above-listed algorithms and additionally the Fish School Search algorithm were used for the development of five different modifications of COBRA by varying the number of component-algorithms. These modifications were tested on the same set of functions and the best of them was found. Ways of further improving the COBRA algorithm are then discussed.
Журнал: IOP CONFERENCE SERIES: MATERIALS SCIENCE AND ENGINEERING
Выпуск журнала: 173
Номера страниц: 012001
Издатель: Institute of Physics Publishing
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