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

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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