| Autor: |
Mateusz Ślażyński, Salvador Abreu, Grzegorz J. Nalepa |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
Electronic Proceedings in Theoretical Computer Science, Vol 306, Iss Proc. ICLP 2019, Pp 168-181 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2075-2180 |
| DOI: |
10.4204/EPTCS.306.22 |
| Popis: |
Local Search meta-heuristics have been proven a viable approach to solve difficult optimization problems. Their performance depends strongly on the search space landscape, as defined by a cost function and the selected neighborhood operators. In this paper we present a logic programming based framework, named Noodle, designed to generate bespoke Local Search neighborhoods tailored to specific discrete optimization problems. The proposed system consists of a domain specific language, which is inspired by logic programming, as well as a genetic programming solver, based on the grammar evolution algorithm. We complement the description with a preliminary experimental evaluation, where we synthesize efficient neighborhood operators for the traveling salesman problem, some of which reproduce well-known results. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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