Name
Title | ||
|---|---|---|
A Novel Opposition-Based Multi-objective Differential Evolution Algorithm for Multi-objective Optimization |
Abstract | ||
|---|---|---|
Multiobjective optimization is of increasing importance in various fields and has very broad applications. The purpose of this paper is to describe a novel multiobjective optimization algorithm---opposition-based multi-objective differential evolution algorithm(OMODE). In the paper, OMODE uses the opposition-based population to generate the initial population of points, The important scaling factor is controlled by self-adaptive method. Performance of OMODE is demonstrated with a set of benchmark test functions and Earth-Mars double transfer problem. The results show that OMODE achieves better performance than other methods. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-92137-0_18 | ISICA |
Keywords | Field | DocType |
opposition-based population,novel opposition-based multi-objective differential,self-adaptive method,benchmark test function,novel multiobjective optimization algorithm,evolution algorithm,multi-objective optimization,broad application,important scaling factor,opposition-based multi-objective differential evolution,multiobjective optimization,better performance,initial population,differential evolution,multi objective optimization | Scale factor,Transfer problem,Population,Mathematical optimization,Vector optimization,Meta-optimization,Multi-objective optimization,Multi-swarm optimization,Differential evolution,Mathematics | Conference |
Volume | ISSN | Citations |
5370 | 0302-9743 | 7 |
PageRank | References | Authors |
0.46 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Peng | 1 | 29 | 7.36 |
| Yuanzhen Wang | 2 | 86 | 11.78 |
| Guangming Dai | 3 | 53 | 14.52 |