Hybrid Swarm and Agent-Based Evolutionary Optimization
| Autor: | Marcin Sendera, Adam Szlachta, Aleksander Byrski, Mateusz Paciorek, Marek Kisiel-Dorohinicki, Leszek Placzkiewicz, Mateusz Godzik |
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| Rok vydání: | 2018 |
| Předmět: |
Mathematical optimization
education.field_of_study Computer science Population Particle swarm optimization 020206 networking & telecommunications 02 engineering and technology ComputingMethodologies_ARTIFICIALINTELLIGENCE 0202 electrical engineering electronic engineering information engineering Benchmark (computing) Memetic algorithm 020201 artificial intelligence & image processing Hybrid swarm education Metaheuristic Selection (genetic algorithm) |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783319937007 ICCS (2) |
| DOI: | 10.1007/978-3-319-93701-4_7 |
| Popis: | In this paper a novel hybridization of agent-based evolutionary system (EMAS, a metaheuristic putting together agency and evolutionary paradigms) is presented. This method assumes utilization of particle swarm optimization (PSO) for upgrading certain agents used in the EMAS population, based on agent-related condition. This may be perceived as a method similar to local-search already used in EMAS (and many memetic algorithms). The obtained and presented in the end of the paper results show the applicability of this hybrid based on a selection of a number of 500 dimensional benchmark functions, when compared to non-hybrid, classic EMAS version. |
| Databáze: | OpenAIRE |
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