Mateusz Ślażyński (AGH University of Science and Technology) |
Salvador Abreu (University of Évora and LISP ) |
Grzegorz J. Nalepa (AGH University of Science and Technology) |
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. |
ArXived at: https://dx.doi.org/10.4204/EPTCS.306.22 | bibtex | |
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