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Combining Answer Set Programming and domain heuristics for solving hard industrial problems (Application Paper)

Published online by Cambridge University Press:  14 October 2016

CARMINE DODARO
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: [email protected])
PHILIP GASTEIGER
Affiliation:
Alpen-Adria-Universität Klagenfurt, Austria (e-mail: [email protected])
NICOLA LEONE
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: [email protected])
BENJAMIN MUSITSCH
Affiliation:
Alpen-Adria-Universität Klagenfurt, Austria (e-mail: [email protected])
FRANCESCO RICCA
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: [email protected])
KOSTYANTYN SHCHEKOTYKHIN
Affiliation:
Alpen-Adria-Universität Klagenfurt, Austria (e-mail: [email protected])

Abstract

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.

Type
Regular Papers
Copyright
Copyright © Cambridge University Press 2016 

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