Name
Title | ||
|---|---|---|
An Effective Variable Neighborhood Search With Perturbation For Location-Routing Problem |
Abstract | ||
|---|---|---|
Location-Routing Problem (LRP) is a challenging problem in logistics, which combines two types of decision: facility location and vehicle routing. In this paper, we focus on LRP with multiple capacitated depots and one uncapacitated vehicle per depot, which has practical applications such as mail delivery and waste collection. We propose a simple iterated variable neighborhood search with an effective perturbation strategy to solve the LRP variant. The experiments show that the algorithm is efficient and can compute better solutions than previous algorithms on tested instances. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1142/S0218213019500246 | INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS |
Keywords | Field | DocType |
Combinatorial optimization, heuristic search, location-routing problem | Variable neighborhood search,Computer science,Theoretical computer science,Artificial intelligence,Perturbation (astronomy),Machine learning | Journal |
Volume | Issue | ISSN |
28 | 7 | 0218-2130 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hua Jiang | 1 | 0 | 0.34 |
| Corinne Lucet | 2 | 99 | 8.51 |
| Laure Devendeville | 3 | 45 | 3.02 |
| Chu Min Li | 4 | 1194 | 85.65 |