An Adaptive Large Neighborhood Search Method to Plan Patient's Journey in Healthcare - Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. IFIP WG 5.7 International Conference. Part II Access content directly
Conference Papers Year : 2021

An Adaptive Large Neighborhood Search Method to Plan Patient's Journey in Healthcare

Abstract

In this paper an adaptation of the Adaptive Large Neighborhood Search (ALNS) to a patient’s care planning problem is proposed. We formalize it as an RCPSP problem that consists of assigning a start date and medical resources to a set of medical appointments. Different intensification and diversification movements for the ALNS are presented. We test this approach on real-life problems and compare the results of ALNS to a version without the adaptive layer, called (¬A)LNS. We also compare our results with the ones obtained with a 0–1 linear programming model. On small instances, ALNS obtains results close to optimality, with an average difference of 1.39 of solution quality. ALNS outperforms (¬A)LNS with a gain of up to 18.34% for some scenarios.
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hal-03611359 , version 1 (13-09-2023)

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Olivier Gerard, Corinne Lucet, Laure Brisoux Devendeville, Sylvain Darras. An Adaptive Large Neighborhood Search Method to Plan Patient's Journey in Healthcare. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2021, Nantes, France. pp.289-297, ⟨10.1007/978-3-030-85902-2_31⟩. ⟨hal-03611359⟩
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