Combining Answer Set Programming and Domain Heuristics for Solving Hard Industrial Problems (Application Paper)
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Abstract (arXiv)
Answer Set Programming (ASP) is a popular logic programming paradigm that has been applied for solving a variety of complex problems. Among the most challenging real-world applications of ASP are two industrial problems defined by Siemens: the Partner Units Problem (PUP) and the Combined Configuration Problem (CCP). The hardest instances of PUP and CCP are out of reach for state-of-the-art ASP solvers. Experiments show that the performance of ASP solvers could be significantly improved by embedding domain-specific heuristics, but a proper effective integration of such criteria in off-the-shelf ASP implementations is not obvious. In this paper the combination of ASP and domain-specific heuristics is studied with the goal of effectively solving real-world problem instances of PUP and CCP. As a byproduct of this activity, the ASP solver WASP was extended with an interface that eases embedding new external heuristics in the solver. The evaluation shows that our domain-heuristic-driven ASP solver finds solutions for all the real-world instances of PUP and CCP ever provided by Siemens. This paper is under consideration for acceptance in TPLP.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Aug 2016.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 2; 2024: 1; 2025: 0; 2026: 1.
8 papers.
- 2023Neuro-Symbolic AI for Compliance Checking of Electrical Control Panelscited by 6
- 2021Lifting Symmetry Breaking Constraints with Inductive Logic Programmingcited by 4
- 2022Efficient lifting of symmetry breaking constraints for complex combinatorial problemscited by 2
- 2022Specifying and Exploiting Non-Monotonic Domain-Specific Declarative Heuristics in Answer Set Programmingcited by 2
- 2024Large Neighborhood Prioritized Search for Combinatorial Optimization with Answer Set Programmingcited by 1
- 2022A Model-Oriented Approach for Lifting Symmetries in Answer Set Programmingcited by 0
- 2023Inductive Learning of Declarative Domain-Specific Heuristics for ASPcited by 0
- 2026EZASP - Facilitating the Usage of ASPcited by 0
- 2026EZASP - Facilitating the Usage of ASP27 Mar 2026
- 2024Large Neighborhood Prioritized Search for Combinatorial Optimization with Answer Set Programming18 May 2024
- 2023Inductive Learning of Declarative Domain-Specific Heuristics for ASP30 Aug 2023
- 2023Neuro-Symbolic AI for Compliance Checking of Electrical Control Panels17 May 2023
- 2022Specifying and Exploiting Non-Monotonic Domain-Specific Declarative Heuristics in Answer Set Programming19 Sep 2022
- 2022A Model-Oriented Approach for Lifting Symmetries in Answer Set Programming5 Aug 2022
- 2022Efficient lifting of symmetry breaking constraints for complex combinatorial problems14 May 2022
- 2021Lifting Symmetry Breaking Constraints with Inductive Logic Programming22 Dec 2021