Collaborative Variable Neighborhood Search

Details

Serval ID
serval:BIB_9315E4F4A1CC
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Collaborative Variable Neighborhood Search
Title of the conference
Lecture Notes in Computer Science
Author(s)
Zufferey N., Gallay O.
Publisher
Springer International Publishing
ISBN
9783319916408
9783319916415
ISSN
0302-9743
1611-3349
Publication state
Published
Issued date
2018
Peer-reviewed
Oui
Pages
320-332
Language
english
Abstract
Variable neighborhood search (VNS) is a well-known metaheuristic. Two main ingredients are needed for its design: a collection M=(N1,…,Nr) 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., Ni 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).
Keywords
Metaheuristics, Variable neighborhood search
Create date
12/06/2018 10:08
Last modification date
21/08/2019 6:12
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