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Optimization with constraints using a cultured differential evolution approach
| Content Provider | CiteSeerX |
|---|---|
| Author | Becerra, Ricardo Landa Coello, Carlos A. Coello |
| Description | In this paper we propose a cultural algorithm, where different knowledge sources modify the variation operator of a differential evolution algorithm. Differential evolution is used as a basis for the population, variation and selection processes. The experiments performed show that the cultured differential evolution is able to reduce the number of fitness function evaluations needed to obtain a good aproximation of the optimum value in constrained real-parameter optimization. Comparisons are provided with respect to three techniques that are representative of the state-of-the-art in the area. |
| File Format | |
| Language | English |
| Publisher Institution | In Proceedings of the GECCO Conference |
| Access Restriction | Open |
| Subject Keyword | Optimum Value Different Knowledge Source Selection Process Cultural Algorithm Constrained Real-parameter Optimization Variation Operator Cultured Differential Evolution Differential Evolution Algorithm Differential Evolution Fitness Function Evaluation Good Aproximation Cultured Differential Evolution Approach |
| Content Type | Text |
| Resource Type | Article |
