Work

Function optimization using metaheuristics

Year: 2006

Type: article

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.

Authors: Marek Pilski, Franciszek Seredyński

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W336630483

FWCI:

Cites: 9

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Related to: 10