Name
Title | ||
|---|---|---|
Reactive Max-Min Ant System With Recursive Local Search And Its Application To Tsp And Qap |
Abstract | ||
|---|---|---|
Ant colony optimization is a successful metaheuristic for solving combinatorial optimization problems. However, the drawback of premature exploitation arises in ant colony optimization when coupled with local searches, in which the neighborhood's structures of the search space are not completely traversed. This paper proposes two algorithmic components for solving the premature exploitation, i.e. the reactive heuristics and recursive local search technique. The resulting algorithm is tested on two well-known combinatorial optimization problems arising in the artificial intelligence problems field and compared experimentally to six (6) variants of ACO with local search. Results showed that the enhanced algorithm outperforms the six ACO variants. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1080/10798587.2016.1177914 | INTELLIGENT AUTOMATION AND SOFT COMPUTING |
Keywords | Field | DocType |
Optimization, combinatorial problems, metaheuristics, swarm intelligence, search algorithms, ant colony optimization, recursive local search, reactive heuristics, traveling salesman problem, quadratic assignment problem | Ant colony optimization algorithms,Mathematical optimization,Guided Local Search,Parallel metaheuristic,Computer science,Combinatorial optimization,Artificial intelligence,Local search (optimization),Machine learning,Iterated local search,Tabu search,Metaheuristic | Journal |
Volume | Issue | ISSN |
23 | 1 | 1079-8587 |
Citations | PageRank | References |
1 | 0.38 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rafid Sagban | 1 | 1 | 0.38 |
| Ku Ruhana Ku Mahamud | 2 | 22 | 9.33 |
| Muhamad Shahbani Abu Bakar | 3 | 1 | 0.72 |