Name
Abstract | ||
|---|---|---|
Differential evolution DE is an efficient population-based stochastic search algorithm, which has shown good search abilities on many real-world and benchmark optimisation problems. In this paper, we propose a new multi-population-based DE MDE algorithm. In MDE, the original population is divided into multiple subpopulations. For each subpopulation, two DE mutation schemes are alternatives to be conducted. Moreover, a Cauchy mutation operator is utilised to enhance the global search. To verify the performance of MDE, 12 well-known benchmark functions are used in the experiments. Simulation results show that MDE performs better than the standard DE and several other DE variants. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1504/IJCSM.2015.067546 | International Journal of Computing Science and Mathematics |
Keywords | Field | DocType |
differential evolution, multi-population, Cauchy mutation, global optimisation | Population,Mathematical optimization,Search algorithm,Computer science,Differential evolution,Cauchy mutation,Operator (computer programming) | Journal |
Volume | Issue | ISSN |
6 | 1 | 1752-5055 |
Citations | PageRank | References |
2 | 0.37 | 12 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhihong Zhang | 1 | 2 | 3.75 |