自动将约束问题转为局部搜索邻域，省去人工设计环节。
Transforming Constraint Programs to Input for Local Search
- 利用约束问题的对称性生成搜索邻域
- 在6个经典问题上验证了生成邻域的有效性
- 适合需要快速构建优化算法的研究者
将局部搜索算法应用于组合优化问题颇具挑战，通常需人工将约束转换为元启发式算法的输入数据。本文建立了约束优化问题的对称性与局部搜索邻域之间的联系，并在此基础上，利用IDP系统从约束规范自动生成邻域。我们对六个经典优化问题评估了所得邻域，结果表明该技术具有可行性。
原文摘要 · Abstract (English)
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. In this paper, we establish a link between symmetry properties of constraint optimization problems and local search neighborhoods, and we use this link to automatically generate neighborhoods from a constraint specification in the context of the IDP system. We evaluate the obtained neighborhoods for six classical optimization problems. The resulting observations support the viability of this technique.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。