Conjure: Automatic Generation of Constraint Models from Problem Specifications
作者:
摘要
When solving a combinatorial problem, the formulation or model of the problem is critical to the efficiency of the solver. Automating the modelling process has long been of interest because of the expertise and time required to produce an effective model of a given problem. We describe a method to automatically produce constraint models from a problem specification written in the abstract constraint specification language Essence. Our approach is to incrementally refine the specification into a concrete model by applying a chosen refinement rule at each step. Any non-trivial specification may be refined in multiple ways, creating a space of models to choose from.
论文关键词:Constraint modelling,Constraint programming,Combinatorial optimization,Constraint satisfaction problem
论文评审过程:Received 22 November 2021, Revised 23 May 2022, Accepted 6 June 2022, Available online 9 June 2022, Version of Record 14 June 2022.
论文官网地址:https://doi.org/10.1016/j.artint.2022.103751