ALASPO: An Adaptive Large-Neighbourhood ASP Optimiser

ALASPO : An Adaptive Large-Neighbourhood ASP Optimiser

Eiter, Thomas (author): Institute for Logic and Computation, TU Wien, Vienna, Austria

Geibinger, Tobias (author): Institute for Logic and Computation, TU Wien, Vienna, Austria

Higuera, Nelson (author): Institute for Logic and Computation, TU Wien, Vienna, Austria

Musliu, Nysret (author): Institute for Logic and Computation, TU Wien, Vienna, Austria; CD-Lab Artis, TU Wien, Austria

Oetsch, Johannes (author): Institute for Logic and Computation, TU Wien, Vienna, Austria

(creator_code:org_t)

Abstract Subject headings

We present the system ALASPO which implements Adaptive Large-neighbourhood search for Answer Set Programming (ASP) Optimisation. Large-neighbourhood search (LNS) is a meta-heuristic where parts of a solution are destroyed and reconstructed in an attempt to improve an overall objective. ALASPO currently supports the ASP solver clingo, as well as its extensions clingo-dl and clingcon for difference and full integer constraints, and multi-shot solving for an efficient implementation of the LNS loop. Neighbourhoods can be defined in code or declaratively as part of the ASP encoding. While the method underlying ALASPO has been described in previous work, ALASPO also incorporates portfolios for the LNS operators along with self-adaptive selection strategies as a technical novelty. This improves usability considerably at no loss of solution quality, but on the contrary often yields benefits. To demonstrate this, we evaluate ALASPO on different optimisation benchmarks.

NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

By the author/editor: Eiter, Thomas; Geibinger, Tobia ...; Higuera, Nelson; Musliu, Nysret; Oetsch, Johannes; Stepanova, Daria

About the subject

NATURAL SCIENCES: NATURAL SCIENCES; and Computer and Inf ...; and Computer Science ...

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