Name
Title | ||
|---|---|---|
Metaheuristics with Local Search Miscellany Applied to the Quadratic Assignment Problem for Large-Scale Instances |
Abstract | ||
|---|---|---|
The quadratic assignment problem (QAP) is classified as an NP-hard problem, so metaheuristic procedures are often used to solve it. QAP is a classic combinatorial optimization problem with real applications, for example in supply chain, logistics, manufacturing, finance, among others. In this article, to search for QAP solutions, the design of a program code for the Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic was implemented with three different neighborhood structures contained in k-exchange mode in order to perform the local search. The experimental procedure was applied for large-scale test instances available from QAPLIB. Finally, the results of the approximations to the optimal solutions are reported. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/978-3-030-86702-7_28 | APPLIED COMPUTER SCIENCES IN ENGINEERING, WEA 2021 |
Keywords | DocType | Volume |
Metaheuristics, NP-hard, k-exchange, Neighborhood | Conference | 1431 |
ISSN | Citations | PageRank |
1865-0929 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rogelio Gonzalez Velazquez | 1 | 3 | 5.17 |
| Erika Granillo-Martínez | 2 | 0 | 0.34 |
| Beatriz Bernábe Loranca | 3 | 7 | 7.45 |
| Jairo E. Powell-González | 4 | 0 | 0.34 |