Name
Title | ||
|---|---|---|
Competitive Coevolution with K-Random Opponents for Pareto Multiobjective Optimization |
Abstract | ||
|---|---|---|
In this paper, our objective is to conduct comprehensive tests for competitive coevolution using an evolutionary multiobjective algorithm for 3 dimensional problems. This competitive coevolution will be implemented with K-Random Opponents strategy. A new algorithm which integrates Competitive Coevolution (CE) and the Strength Pareto Evolutionary Algorithm 2 (SPEA2) is proposed to achieve this objective. The resulting algorithm is referred to as the Strength Pareto Evolutionary Algorithm 2 with Competitive Coevolution (SPEA2-CE). The performance between SPEA2-CE is compared against SPEA2 to solve problems with each having three objectives using DTLZ suite of test problems. In general, the results show that the SPEA2-CE with K-Random Opponents performed well for the generational distance and coverage but performed less favorably for spacing. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICNC.2007.309 | ICNC |
Keywords | Field | DocType |
dtlz suite,k-random opponents,evolutionary multiobjective algorithm,pareto multiobjective optimization,resulting algorithm,comprehensive test,new algorithm,strength pareto evolutionary algorithm,k-random opponents strategy,competitive coevolution,dimensional problem,3 dimensional,evolutionary computation,multiobjective optimization,coevolution | Competitive coevolution,Mathematical optimization,Suite,Evolutionary algorithm,Computer science,Generational distance,Evolutionary computation,Multi-objective optimization,Artificial intelligence,Pareto principle,Machine learning | Conference |
Volume | ISSN | ISBN |
4 | 2157-9555 | 0-7695-2875-9 |
Citations | PageRank | References |
1 | 0.35 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tse Guan Tan | 1 | 17 | 3.52 |
| Jason Teo | 2 | 24 | 5.00 |
| HuiKeng Lau | 3 | 23 | 5.43 |