Function optimization using metaheuristics

• Autorzy: Pilski M. , Seredyński F.
• Języki publikacji: EN

Abstrakty

EN

The paper presents the results of comparison of three metaheuristics that currently exist in the problem of function optimization. The first algorithm is Particle Swarm Optimization (PSO) - the algorithm has recently emerged. The next one is based on a paradigm of Artificial Immune System (AIS). Both algorithms are compared with Genetic Algorithm (GA). The algorithms are applied to optimize a set of functions well known in the area of evolutionary computation. Experimental results show that it is difficult to unambiguously select one best algorithm which outperforms other tested metaheuristics.

Słowa kluczowe

EN

particle swarm optimization (PSO); artificial immune system; genetic algorithm; function optimization

• Wydawca: Wydawnictwo Uniwersytetu Przyrodniczo-Humanistycznego w Siedlcach
• Czasopismo: Studia Informatica : systems and information technology
• Rocznik: 2006
• Tom: Vol. 1(7)
• Strony: 77--91
• Opis fizyczny: Bibliogr. 16 poz., wykr.

Twórcy

autor

Pilski M.

• Institute of Computer Sciences, University of Podlasie, Sienkiewicza 51, 08-110 Siedlce, Poland

autor

Seredyński F.

• Institute of Computer Sciences, University of Podlasie, Sienkiewicza 51, 08-110 Siedlce, Poland
• Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008 Warsaw, Poland
• Institute of Computer Science, Polish Academy of Sciences, Ordona 21, 01-237 Warsaw, Poland

Bibliografia

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