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Explanation-based large neighborhood search

Content Provider	Springer Nature Link
Author	Prud’homme, Charles Lorca, Xavier Jussien, Narendra
Copyright Year	2014
Abstract	One of the most well-known and widely used local search techniques for solving optimization problems in Constraint Programming is the Large Neighborhood Search (LNS) algorithm. Such a technique is, by nature, very flexible and can be easily integrated within standard backtracking procedures. One of its drawbacks is that the relaxation process is quite often problem dependent. Several works have been dedicated to overcome this issue through problem independent parameters. Nevertheless, such generic approaches need to be carefully parameterized at the instance level. In this paper, we demonstrate that the issue of finding a problem independent neighborhood generation technique for LNS can be addressed using explanation-based neighborhoods. An explanation is a subset of constraints and decisions which justifies a solver event such as a domain modification or a conflict. We evaluate our proposal for a set of optimization problems. We show that our approach is at least competitive with or even better than state-of-the-art algorithms and can be easily combined with state-of-the-art neighborhoods. Such results pave the way to a new use of explanation-based approaches for improving search.
Starting Page	339
Ending Page	379
Page Count	41
File Format	PDF
ISSN	13837133
Journal	Constraints
Volume Number	19
Issue Number	4
e-ISSN	15729354
Language	English
Publisher	Springer US
Publisher Date	2014-07-20
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	LNS Explanations Optimization Neighborhoods Artificial Intelligence (incl. Robotics) Computing Methodologies Operations Research/Decision Theory
Content Type	Text
Resource Type	Article
Subject	Discrete Mathematics and Combinatorics Artificial Intelligence Computational Theory and Mathematics Software

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