Large neighbourhood search with adaptive guided ejection search for the pickup and delivery problem with time windows

Timothy Curtois, Dario Landa-silva, Yi Qu, Wasakorn Laesanklang

    Research output: Contribution to journalArticlepeer-review

    15 Citations (Scopus)

    Abstract

    An effective and fast hybrid metaheuristic is proposed for solving the pickup and delivery problem with time windows. The proposed approach combines local search, large neighbourhood search and guided ejection search in a novel way to exploit the benefits of each method. The local search component uses a novel neighbourhood operator. A streamlined implementation of large neighbourhood search is used to achieve an effective balance between intensification and diversification. The adaptive ejection chain component perturbs the solution and uses increased or decreased computation time according to the progress of the search. While the local search and large neighbourhood search focus on minimising travel distance, the adaptive ejection chain seeks to reduce the number of routes. The proposed algorithm design results in an effective and fast solution method that finds a large number of new best-known solutions on a well-known benchmark dataset. Experiments are also performed to analyse the benefits of the components and heuristics and their combined use to achieve a better understanding of how to better tackle the subject problem.
    Original languageEnglish
    Pages (from-to)151-192
    JournalEURO Journal on Transportation and Logistics
    Volume7
    Issue number2
    Early online date12 Jan 2018
    DOIs
    Publication statusPublished - Jun 2018

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