Affiliation:
1. Department of Electrical, Electronic and Information Engineering “G. Marconi”, University of Bologna, Bologna 40136, Italy;
2. Interdepartmental Center for Industrial Research on Information and Communication Technologies, University of Bologna, Cesena 47521, Italy
Abstract
In this paper, we propose a fast and scalable, yet effective, metaheuristic called FILO to solve large-scale instances of the Capacitated Vehicle Routing Problem. Our approach consists of a main iterative part, based on the Iterated Local Search paradigm, which employs a carefully designed combination of existing acceleration techniques, as well as novel strategies to keep the optimization localized, controlled, and tailored to the current instance and solution. A Simulated Annealing-based neighbor acceptance criterion is used to obtain a continuous diversification, to ensure the exploration of different regions of the search space. Results on extensively studied benchmark instances from the literature, supported by a thorough analysis of the algorithm’s main components, show the effectiveness of the proposed design choices, making FILO highly competitive with existing state-of-the-art algorithms, both in terms of computing time and solution quality. Finally, guidelines for possible efficient implementations, algorithm source code, and a library of reusable components are open-sourced to allow reproduction of our results and promote further investigations.
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Subject
Transportation,Civil and Structural Engineering
Cited by
32 articles.
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