Transforming Constraint Programs to Input for Local Search
The paper discusses the transformation of constraint programs into input for local search algorithms. It highlights the challenges of applying local search to combinatorial optimization problems and proposes a method to automate the generation of neighborhoods from constraint specifications. The authors evaluate their approach on six classical optimization problems, demonstrating its effectiveness.
- ▪The paper establishes a link between symmetry properties of constraint optimization problems and local search neighborhoods.
- ▪This research aims to automate the process of generating neighborhoods for local search algorithms.
- ▪The technique was evaluated on six classical optimization problems, showing promising results.
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Computer Science > Artificial Intelligence arXiv:2605.19671 (cs) [Submitted on 19 May 2026] Title:Transforming Constraint Programs to Input for Local Search Authors:Jo Devriendt, Patrick De Causmaecker, Marc Denecker View a PDF of the paper titled Transforming Constraint Programs to Input for Local Search, by Jo Devriendt and 2 other authors View PDF HTML (experimental) Abstract:Applying local search algorithms to combinatorial optimization problems is not an easy feat. Typically, human intervention is required to compile the constraints to input data for some metaheuristic algorithm.
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