@inproceedings{a5b6fc3bf33e404e88f4c25f93626ea3,
title = "Variable-Relationship Guided LNS for the Car Sequencing Problem",
abstract = "Large Neighbourhood Search (LNS) is a powerful technique that applies the “divide and conquer” principle to boost the performance of solvers on large scale Combinatorial Optimization Problems. In this paper we consider one of the main hindrances to the LNS popularity, namely the requirement of an expert to define a problem specific neighborhood. We present an approach that learns from problem structure and search performance in order to generate neighbourhoods that can match the performance of domain specific heuristics developed by an expert. Furthermore, we present a new objective function for the optimzation version of the Car Sequencing Problem, that better distinguishes solution quality. Empirical results on public instances demonstrate the effectiveness of our approach against both a domain specific heuristic and state-of-the-art generic approaches.",
keywords = "Car sequencing problem, LNS, Neighbourhood selection",
author = "Filipe Souza and Diarmuid Grimes and Barry O{\textquoteright}Sullivan",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s).; 30th Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2022 ; Conference date: 08-12-2022 Through 09-12-2022",
year = "2023",
doi = "10.1007/978-3-031-26438-2\_34",
language = "English",
isbn = "9783031264375",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "437--449",
editor = "Luca Longo and Ruairi O{\textquoteright}Reilly",
booktitle = "Artificial Intelligence and Cognitive Science - 30th Irish Conference, AICS 2022, Revised Selected Papers",
address = "Germany",
}