Use of domain information to improve the performance of an evolutionary algorithm | Zendy

Ricardo Landa Becerra | Zendy; Carlos A. Coello Coello | Zendy

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Use of domain information to improve the performance of an evolutionary algorithm

Author(s) -

Ricardo Landa Becerra,

Carlos A. Coello Coello

Publication year - 2005

Publication title -

citeseer x (the pennsylvania state university)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1145/1102256.1102337

Subject(s) - cultural algorithm , evolutionary algorithm , evolutionary computation , computer science , domain (mathematical analysis) , focus (optics) , mathematical optimization , multi objective optimization , fitness function , computation , interactive evolutionary computation , evolutionary music , optimization problem , algorithm , artificial intelligence , genetic algorithm , machine learning , meta optimization , evolutionary programming , mathematics , mathematical analysis , physics , optics

The main goal of this thesis work is to explore the capacities of cultural algorithms to add domain knowledge in evolutionary computation. Within our objectives is to develop a cultural algorithm for constrained optimization, and other for multiobjective optimization. With a proper desing of the belief space we expect to obtain competitive results compared with other state-of-the-art evolutionary algorithms, but reducing the number of fitness function evaluations needed. In this paper we focus in the algorithm for constrained optimization, because the development of the algorithm for multiobjective optimzation is an early stage.

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