Name
Abstract | ||
|---|---|---|
Immune Evolutionary Algorithm (IEA) is proposed on the shortages of evolution algorithm and biological immune mechanism. According to the characteristics of chaos, a novel Chaotic Immune Evolutionary Algorithm (CIEA) is presented which introduces chaos to IEA. The algorithm has the merits of chaos, immunity and evolutionary algorithm. It can ensure the ability of global search and local search and enhance the performances of the algorithm. At last, we analyze the efficiency of the algorithm with two typical optimization problems. The analysis result shows that CIEA converges quickly and effectively avoids the inherent problem that the evolution algorithm traps in immature convergence, so CIEA is an effective way to solve complex optimization problem. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11539117_125 | ICNC (2) |
Keywords | Field | DocType |
complex optimization problem,evolution algorithm,inherent problem,evolutionary algorithm,chaotic immune evolutionary algorithm,optimization method,novel chaotic immune evolutionary,immune evolutionary algorithm,global search,typical optimization problem,evolution algorithm trap,local search,optimization problem | Convergence (routing),Mathematical optimization,Artificial immune system,Evolutionary algorithm,Computer science,Algorithm,Local search (optimization),Chaotic,Economic shortage,Optimization problem,Genetic algorithm | Conference |
Volume | ISSN | ISBN |
3611 | 0302-9743 | 3-540-28325-0 |
Citations | PageRank | References |
1 | 0.40 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yong Chen | 1 | 52 | 12.67 |
| Xiyue Huang | 2 | 12 | 3.91 |