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.
We present several refinements of compound-move generation and show its very positive impact on several third-party models. This helps reduce the unavoidable gap between black-box local search and local-search algorithms crafted by experts.
This work is supported by the Swedish Research Council (VR) through Project Grant 2015-04910.
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Notes
- 1.
Note that upon also considering the semantics of the
constraint in line 5, a backend that only explores assignments satisfying that constraint can infer that the
are in fact functionally determined by line 10. However, to the best of our knowledge, no backend to MiniZinc performs such a semantic analysis. Also, doing so would not address all cases where a model can be seen as having non-functionally determined variables representing auxiliary information. - 2.
- 3.
constraint in line 5, a backend that only explores assignments satisfying that constraint can infer that the
are in fact functionally determined by line 10. However, to the best of our knowledge, no backend to MiniZinc performs such a semantic analysis. Also, doing so would not address all cases where a model can be seen as having non-functionally determined variables representing auxiliary information.References
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Björdal, G., Flener, P., Pearson, J. (2019). Generating Compound Moves in Local Search by Hybridisation with Complete Search. In: Rousseau, LM., Stergiou, K. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2019. Lecture Notes in Computer Science(), vol 11494. Springer, Cham. https://doi.org/10.1007/978-3-030-19212-9_7
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