Reduce and assign: A constraint logic programming and local search integration framework to solve combinatorial search problems

Abstract

Since the early 90's that Constraint Logic Programming (CLP) has been used to solve Combinatorial Search Problems. Generally, CLP has a good performance with highly constrained problems, but it lacks a "global perspective" of the search space, making the search for the optimal solution more difficult when the problems becomes larger and less constrained. On the other hand, Local Search Methods explore the search space directly through an " intelligent" construction of solution neighbourhoods, turning these methods suitable for solving less constrained and large search spaces problems. The aim of this paper is to present a hybridisation framework that allows combining Local Search methods with Constraint Logic Programming. The first results demonstrate that while maintaining the CLP strengths it is possible to overcome their weaknesses and improve its search efficiency. © Springer-Verlag 2003.