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

Timothy Curtois (), Dario Landa-Silva (), Yi Qu () and Wasakorn Laesanklang ()
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Timothy Curtois: The University of Nottingham
Dario Landa-Silva: The University of Nottingham
Yi Qu: The University of Nottingham
Wasakorn Laesanklang: The University of Nottingham

EURO Journal on Transportation and Logistics, 2018, vol. 7, issue 2, No 4, 192 pages

Abstract: 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.

Keywords: Large neighbourhood; Guided ejection; Vehicle routing (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s13676-017-0115-6

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