Hybridizing a matheuristic with ALNS for the optimal collection and delivery of medical specimens

Ferone, Daniele, Festa, Paola, Fugaro, Serena and Pastore, Tommaso (2023) Hybridizing a matheuristic with ALNS for the optimal collection and delivery of medical specimens. International Transactions in Operational Research, 32 (1). pp. 90-116. ISSN 0969-6016

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Abstract

The past few years of the COVID-19 pandemic outbreak have shown that optimal management of medical specimens is a key aspect of healthcare logistics, both for addressing the delivery of perishable items such as vaccines, and for ensuring the timely analysis of swabs and samples. Accordingly, recent optimization literature described the problem of optimal collection and delivery of medical specimens, modeled as a multitrip vehicle routing problem with time windows and a completion time objective function. Aiming to achieve good-quality solutions in short computational times, this work describes a hybrid approach, combining a matheuristic construction phase with an adaptive large neighborhood search (ALNS). Our matheuristic relies on a clustering algorithm to yield subsets of the medical specimens that are optimally served by single vehicles of the fleet. The solutions of the matheuristic phase serve as starting points for the ALNS intensification phase. Extensive experimentation on both new and established benchmark problem instances shows that our hybrid method is able to match the optimality of the state of the art on small instances and outperforms the existing exact method by one order of magnitude on larger problems.

Item Type:	Article
Additional Information:	Publisher Copyright: © 2023 The Authors. International Transactions in Operational Research published by John Wiley & Sons Ltd on behalf of International Federation of Operational Research Societies.
Uncontrolled Keywords:	alns,healthcare logistics,matheuristic,multitrip,routing,business and international management,computer science applications,strategy and management,management science and operations research,management of technology and innovation,sdg 3 - good health and well-being ,/dk/atira/pure/subjectarea/asjc/1400/1403
Faculty \ School:	Faculty of Social Sciences > Norwich Business School
Related URLs:	https://www.scopus.com/pages/publication...
Depositing User:	LivePure Connector
Date Deposited:	01 Jun 2026 11:45
Last Modified:	03 Jun 2026 17:15
URI:	https://ueaeprints.uea.ac.uk/id/eprint/103217
DOI:	10.1111/itor.13386

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