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Cluster Computing

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07.04.2022

An improved multi-objective imperialist competitive algorithm for surgical case scheduling problem with switching and preparation times

verfasst von: Hui Yu, Jun-qing Li, Xiao-long Chen, Wei Niu, Hong-yan Sang

Erschienen in: Cluster Computing | Ausgabe 5/2022

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Abstract

Surgical case scheduling is a key issue in the field of medician, which is a challenging work because of the difficulty in assigning resources to patients. This study regards the surgical case scheduling problem as a flexible job shop scheduling problem (FJSP). Considering the switching and preparation time of patients in different stage, an improved multi-objective imperialist competitive algorithm (IMOICA), which adopts the non-dominant sorting method, is proposed to optimize the whole scheduling. First, the social hierarchy strategy is developed to initialize the empire. Then, to enhance the global search ability of the algorithm, the concept of attraction and repulsion (AR) is introduced into the assimilation strategy. Moreover, to increase the diversity of the population, the revolution strategy is utilized. Finally, the variable neighborhood search (VNS) strategy is embedded to improve its exploitation capacity further. Experiments show that scheduling in advance saves time and cost, and IMOICA can solve the surgical case scheduling problem studied efficiently.

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Titel: An improved multi-objective imperialist competitive algorithm for surgical case scheduling problem with switching and preparation times
verfasst von: Hui Yu
Jun-qing Li
Xiao-long Chen
Wei Niu
Hong-yan Sang
Publikationsdatum: 07.04.2022
Verlag: Springer US
Erschienen in: Cluster Computing / Ausgabe 5/2022
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-022-03589-0

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