Name
Abstract | ||
|---|---|---|
Variable neighborhood search (VNS) is a well-known metaheuristic. Two main ingredients are needed for its design: a collection M = (N-1, ..., N-r) of neighborhood structures and a local search LS (often using its own single neighborhood L). M has a diversification purpose (search for unexplored zones of the solution space S), whereas LS plays an intensification role (focus on the most promising parts of S). Usually, the used set M of neighborhood structures relies on the same type of modification (e.g., change the value of i components of the decision variable vector, where i is a parameter) and they are built in a nested way (i.e., N-i is included in Ni+1). The more difficult it is to escape from the currently explored zone of S, the larger is i, and the more capability has the search process to visit regions of S which are distant (in terms of solution structure) from the incumbent solution. M is usually designed independently from L. In this paper, we depart from this classical VNS framework and discuss an extension, Collaborative Variable Neighborhood Search (CVNS), where the design of M and L is performed in a collaborative fashion (in contrast with nested and independent), and can rely on various and complementary types of modifications (in contrast with a common type with different amplitudes). |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-91641-5_27 | BIOINSPIRED OPTIMIZATION METHODS AND THEIR APPLICATIONS, BIOMA 2018 |
Keywords | Field | DocType |
Metaheuristics,Variable neighborhood search | Heuristic,Variable neighborhood search,Computer science,Theoretical computer science,Diversification (marketing strategy),Local search (optimization),Distributed computing | Conference |
Volume | ISSN | Citations |
10835 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicolas Zufferey | 1 | 443 | 28.85 |
| Olivier Gallay | 2 | 8 | 3.06 |