Name
Title | ||
|---|---|---|
A Hybrid Evolutionary Algorithm With Taboo And Competition Strategies For Minimum Vertex Cover Problem |
Abstract | ||
|---|---|---|
The Minimum Vertex Cover (MVC) problem is a prominent NP-hard combinatorial optimization problem, which is of great significance in both theory and application. Evolutionary algorithms and local search algorithms have proved to be two important methods to solve this problem. However, the combination of these two methods does not perform well. In order to acquire an effective hybrid evolutionary algorithm, two new control strategies are proposed, which are taboo of solution-distance and intensive competition of individuals. A hybrid evolutionary algorithm for the MVC problem, referred to HETC, is proposed in this paper using these two strategies. The effectiveness of the proposed scheme is validated by conducting deep simulations. The results obtained by the proposed scheme are compared with results obtained by EWSL, the state-of-the-art algorithm, and NuMVC. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/978-3-030-36808-1_79 | NEURAL INFORMATION PROCESSING (ICONIP 2019), PT IV |
Keywords | DocType | Volume |
Evolutionary algorithms, Estimation of Distribution Algorithms, Local search, Guiding strategy, Minimum Vertex Cover (MVC) | Conference | 1142 |
ISSN | Citations | PageRank |
1865-0929 | 0 | 0.34 |
References | Authors | |
7 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gang Yang | 1 | 32 | 9.38 |
| Daopeng Wang | 2 | 0 | 0.34 |
| Jieping Xu | 3 | 4 | 1.77 |