Name
Title | ||
|---|---|---|
Reactive Search strategies using Reinforcement Learning, local search algorithms and Variable Neighborhood Search. |
Abstract | ||
|---|---|---|
•The proposed algorithm has a stable behavior with standard deviation lesser than 0.5%.•Two instances from the TSPLIB are 100% optimal, 3 are over 99%, 4 are over 97%.•The proposed method has superior performance in all instances to the values of O.F.•The performance of processing time of the proposed algorithm is superior to all other. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.eswa.2014.01.040 | Expert Systems with Applications |
Keywords | Field | DocType |
Reactive Search,Reinforcement Learning,Local search,Variable Neighborhood Search,Combinatorial optimization | Guided Local Search,Variable neighborhood search,Computer science,Hyper-heuristic,Artificial intelligence,Metaheuristic,Mathematical optimization,Algorithm,Beam search,Local search (optimization),Tabu search,Machine learning,Best-first search | Journal |
Volume | Issue | ISSN |
41 | 10 | 0957-4174 |
Citations | PageRank | References |
7 | 0.41 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| João Paulo Queiroz dos Santos | 1 | 8 | 0.76 |
| Jorge D. Melo | 2 | 30 | 7.01 |
| Adrião Duarte Dória Neto | 3 | 84 | 15.21 |
| Daniel Aloise | 4 | 344 | 24.21 |