Name
Abstract | ||
|---|---|---|
Differential Evolution (DE) is widely used in real- parameter optimization problems in many domains, such as single objective optimization, constrained optimization, multi-modal optimization, and multi-objective optimization. Self-adaptive DE algorithm, called jDE, was introduced in 2006, and since then many other DE-based algorithms were proposed and many excellent mechanisms have improved DE a lot. In this paper we adopt two mutation strategies into the jDE algorithm. Additionally, the new algorithm (jDErpo) uses a gradually increasing mechanism for controlling lower bound of control parameters, JADE's mechanism for a mutant vector if some their components are out of bounds of a search space. Experimental results of the new algorithm are presented using CEC 2013 benchmark functions. The obtained results show that new mechanisms improve performance of the jDE algorithm and the jDErpo algorithm indicates competitive performance compared with the best DE-based algorithms at CEC 2013. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/SDE.2014.7031537 | Differential Evolution |
Keywords | Field | DocType |
evolutionary computation,search problems,JADE mechanism,constrained optimization,control parameters,differential evolution,jDErpo algorithm,multimodal optimization,multiobjective optimization,mutant vector,mutation strategies,real-parameter optimization problems,search space,self-adaptive jDE algorithm,single objective optimization | Mathematical optimization,Derivative-free optimization,Vector optimization,Computer science,Meta-optimization,Test functions for optimization,Algorithm,Multi-swarm optimization,Imperialist competitive algorithm,Optimization problem,Metaheuristic | Conference |
Citations | PageRank | References |
3 | 0.38 | 22 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Janez Brest | 1 | 46 | 2.97 |
| Ales Zamuda | 2 | 400 | 18.26 |
| Iztok Fister | 3 | 3 | 0.38 |
| Borko Bošković | 4 | 343 | 17.09 |