2019/09/18 by Mateusz Ślażyński
Computer Science · #cs.NE #cs.PL
paper · pdf · doi:10.4204/eptcs.306.59
published as EPTCS 306, 2019, pp. 433-440 · In Proceedings ICLP 2019, arXiv:1909.07646
arxiv created 2019/09/18 · arxiv updated 2019/09/19
Constraint Programming (CP) and Local Search (LS) are different paradigms for dealing with combinatorial search and optimization problems. Their complementary features motivated researchers to create hybrid CP/LS solutions, maintaining both the modeling capabilities of CP and the computational advantages of the heuristic-based LS approach. Research presented in this report is focused on developing a novel method to infer an efficient LS neighborhood operator based on the problem structure, as modeled in the CP paradigm. We consider a limited formal language that we call a Neighborhood Definition Language, used to specify the neighborhood operators in a fine-grained and declarative manner. Together with Logic Programming runtime called Noodle, it allows to automatically synthesize complex operators using a Grammar Evolution algorithm.