# Combining Answer Set Programming and Domain Heuristics for Solving Hard Industrial Problems (Application Paper)

arXiv: https://arxiv.org/abs/1608.00730 · HTML: https://mlsanity.com/paper/1608.00730/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Aug 2016.

## Built on by (most cited first, 8 of 8)

- [Neuro-Symbolic AI for Compliance Checking of Electrical Control Panels](https://mlsanity.com/paper/2305.10113/) (2023)
- [Lifting Symmetry Breaking Constraints with Inductive Logic Programming](https://mlsanity.com/paper/2112.11806/) (2021)
- [Efficient lifting of symmetry breaking constraints for complex combinatorial problems](https://mlsanity.com/paper/2205.07129/) (2022)
- [Specifying and Exploiting Non-Monotonic Domain-Specific Declarative Heuristics in Answer Set Programming](https://mlsanity.com/paper/2209.09066/) (2022)
- [Large Neighborhood Prioritized Search for Combinatorial Optimization with Answer Set Programming](https://mlsanity.com/paper/2405.11305/) (2024)
- [A Model-Oriented Approach for Lifting Symmetries in Answer Set Programming](https://mlsanity.com/paper/2208.03095/) (2022)
- [Inductive Learning of Declarative Domain-Specific Heuristics for ASP](https://mlsanity.com/paper/2308.15863/) (2023)
- [EZASP - Facilitating the Usage of ASP](https://mlsanity.com/paper/2603.26863/) (2026)

## 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.