An iterative auction for resource-constrained surgical scheduling

Lu Liu, Chun Wang, Jian-Jun Wang and Antonio Marcio Ferreira Crespo

Journal of the Operational Research Society, 2023, vol. 74, issue 3, 968-978

Abstract: We consider a decentralized surgical scheduling problem with conflicting multiple renewable resources requirements under surgeon’s private availability restriction. The objective of the surgical scheduling planner is to maximize the weighted sum of the number of potential selected surgeries. Due to the information asymmetry and the efforts taken by self-interest decision makers to maximize their own benefits, the coordination between the surgical schedule planner and surgeons for achieving efficient scheduling is difficult. In order to solve the decentralized surgical scheduling problem, we propose an auction mechanism in which surgeons only need to submit partial availability information when necessary. In the mechanism, surgeons submit bids based on their availability and renewable resources requirements for performing a surgery, while the winner determination model is formulated to select bids when the termination condition of the iterative bidding procedure is not satisfied. Under the proposed mechanism, we prove that myopic bidding is surgeons’ weakly dominant strategy. The results of our computational experiments also show that the proposed mechanism can achieve high efficiency compared with optimal solutions on different supply-demand ratio configurations. We also observed that the privacy loss incurred during the bidding process is negatively correlated to the supply-demand ratio.

Date: 2023
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DOI: 10.1080/01605682.2022.2083988

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