Function optimization using metaheuristics

Authors

  • Marek Pilski
  • Franciszek Seredyński

Abstract

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.

Downloads

Download data is not yet available.

Downloads

Published

2006-12-15

How to Cite

Pilski, M., & Seredyński, F. (2006). Function optimization using metaheuristics. Studia Informatica. System and Information Technology, 7(1-2), 77–91. Retrieved from https://czasopisma.uph.edu.pl/studiainformatica/article/view/2852