A Framework for Constraint Based Local Search using Essence

A Framework for Constraint Based Local Search using Essence

Özgür Akgün, Saad Attieh, Ian P. Gent, Christopher Jefferson, Ian Miguel, Peter Nightingale, András Z. Salamon, Patrick Spracklen, James Wetter

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Main track. Pages 1242-1248. https://doi.org/10.24963/ijcai.2018/173

Structured Neighbourhood Search (SNS) is a framework for constraint-based local search for problems expressed in the Essence abstract constraint specification language.  The local search explores a structured neighbourhood, where each state in the neighbourhood preserves a high level structural feature of the problem. SNS derives  highly structured problem-specific neighbourhoods automatically and directly from the features of the Essence specification of the problem. Hence, neighbourhoods can represent important structural features of the problem, such as partitions of sets, even if that structure is obscured in the low-level input format required by a constraint solver.  SNS expresses each neighbourhood as a constrained optimisation problem, which is solved with a constraint solver. We have implemented SNS, together with automatic generation of neighbourhoods for high level structures, and report high quality results for several optimisation problems.
Keywords:
Constraints and SAT: Constraint Satisfaction
Constraints and SAT: Modeling;Formulation
Constraints and SAT: Constraint Optimisation
Constraints and SAT: Constraints: Solvers and Tools