Online Control of Adaptive Large Neighborhood Search using Deep Reinforcement Learning

arXiv:2211.00759v3 Announce Type: replace
Abstract: The Adaptive Large Neighborhood Search (ALNS) algorithm has shown considerable success in solving combinatorial optimization problems (COPs). Nonetheless, the performance of ALNS relies on the proper configuration of its selection and acceptance parameters, which is known to be a complex and resource-intensive task. To address this, we introduce a Deep Reinforcement Learning (DRL) based approach called DR-ALNS that selects operators, adjusts parameters, and controls the acceptance criterion throughout the search. The proposed method aims to …

abstract algorithm arxiv control cops cs.ai cs.lg optimization parameters performance reinforcement reinforcement learning search success type