Probabilistic-Based Differential Evolution Algorithm
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| Title | Probabilistic-Based Differential Evolution Algorithm |
| Authors | |
| Abstract | – In this paper we propose a probabilistic-based differential evolution (DE) algorithm for solving optimization problems. One of main drawbacks of DE is its few search efforts which it carries out for exploring the search space. The proposed DE with a probability and after providing a better fitness, accepts the generated donor member in mutation stage as an offspring. So the proposed algorithm by a new offspring can obtain a better exploration of the search space without imposing any additional operator. This improved algorithm is applied on some continuous benchmark functions and is compared with some modern and recently proposed differential evolution and other evolutionary algorithms. The obtained results demonstrate that the proposed algorithm has a completely comparable performance than other versions of DE algorithms. In a later part of the comparative experiments, performance comparisons of the proposed algorithm with some other evolutionary algorithms (EAs) shows that it has a better performance than other compared EAs |
| Publisher | World Science Publisher |
| Date | 2013-04-29 |
| Source | XXXX-XXXX |
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