CP-Based Local Branching

We propose the integration and extension of the local branching search strategy in Constraint Programming (CP). Local branching is a general purpose heuristic method which searches locally around the best known solution by employing tree search. It has been successfully used in MIP where local branching constraints are used to model the neighborhood of an incumbent solution and improve the bound. The integration of local branching in CP is not simply a matter of implementation, but requires a number of significant extensions (concerning the computation of the bound, cost-based filtering of the branching constraints, diversification, variable neighbourhood width and search heuristics) and can greatly benefit from the CP environment. In this paper, we discuss how such extensions are possible and provide some experimental results to demonstrate the practical value of local branching in CP.