A multistage optimisation algorithm for the large Vehicle Routing Problem with Time Windows and Synchronised Visits
Polnik, Mateusz and Riccardi, Annalisa and Akartunali, Kerem (2021) A multistage optimisation algorithm for the large Vehicle Routing Problem with Time Windows and Synchronised Visits. Journal of the Operational Research Society, 72 (11). pp. 2396-2411. ISSN 0160-5682 (https://doi.org/10.1080/01605682.2020.1792365)
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Abstract
We propose a multistage algorithm for the Vehicle Routing Problem with Time Windows and Synchronised Visits, which is capable of solving large problem instances arising in Home Health Care applications. The algorithm is based on a Constraint Programming formulation of the daily Home Care Scheduling and Routing Problem. It contains visits with hard time windows and pairwise synchronisation to be staffed by carers who have different skills and work custom shift patterns with contractual breaks. In a computational study, we first experiment with a benchmark set from the literature for the Vehicle Routing Problem with Time Windows and Synchronised Visits. Our algorithm reproduced the majority of the best-known solutions, and strictly improved results for several other instances. Most importantly, we demonstrate that the algorithm can effectively solve real scheduling instances obtained from a UK home care provider. Their size significantly surpass similar scheduling problems considered in the literature. The multistage algorithm solved each of these instances in a matter of minutes, and outperformed human planners, scheduling more visits and significantly reducing total travel time.
ORCID iDs
Polnik, Mateusz, Riccardi, Annalisa ORCID: https://orcid.org/0000-0001-5305-9450 and Akartunali, Kerem ORCID: https://orcid.org/0000-0003-0169-3833;-
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Item type: Article ID code: 73214 Dates: DateEvent2 November 2021Published7 August 2020Published Online2 July 2020AcceptedSubjects: Technology > Mechanical engineering and machinery Department: Faculty of Engineering > Mechanical and Aerospace Engineering
Strathclyde Business School > Management ScienceDepositing user: Pure Administrator Date deposited: 15 Jul 2020 13:26 Last modified: 17 Nov 2024 01:18 URI: https://strathprints.strath.ac.uk/id/eprint/73214