Generating Compound Moves in Local Search by Hybridisation with Complete Search

Gustav Björdal, Pierre Flener, Justin Pearson

Abstract: A black-box local-search backend to a solving-technology-independent modelling language, such as MiniZinc, automatically infers from the structure of a declarative model for a satisfaction or optimisation problem a combination of a neighbourhood, heuristic, and meta-heuristic. These ingredients are then provided to a local-search solver, but are manually designed in a handcrafted local-search algorithm. However, such a backend can perform poorly due to model structure that is inappropriate for local search, for example when it considers moves modifying only variables that represent auxiliary information. Towards overcoming such inefficiency, we propose compound-move generation, an extension to local-search solvers that uses a complete-search solver in order to augment moves modifying non-auxiliary variables so that they also modify auxiliary ones. Since compound-move generation is intended to be applied to such models, we discuss how to identify them.