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

Hui Yu1, Jun-Qing Li2, Xiao-Long Chen1

  • 1School of Information Science and Engineering, Shandong Normal University, Jinan, 250000 People's Republic of China.

Cluster Computing
|April 18, 2022
PubMed
Summary

Optimizing surgical case scheduling using an improved multi-objective imperialist competitive algorithm (IMOICA) reduces time and costs. This advanced algorithm efficiently solves complex scheduling challenges in healthcare resource allocation.

Keywords:
Imperialist competitive algorithmSurgical case schedulingVariable neighborhood search strategy

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Area of Science:

  • Operations Research
  • Healthcare Management
  • Computer Science

Background:

  • Surgical case scheduling is a critical yet complex aspect of healthcare operations.
  • Efficiently assigning limited resources to patients presents significant challenges.
  • Existing methods often struggle to account for dynamic factors like patient preparation times.

Purpose of the Study:

  • To address the complexities of surgical case scheduling by modeling it as a flexible job shop scheduling problem (FJSP).
  • To develop and evaluate an improved multi-objective imperialist competitive algorithm (IMOICA) for optimizing surgical scheduling.
  • To incorporate patient switching and preparation times into the scheduling optimization process.

Main Methods:

  • The study frames surgical case scheduling as a flexible job shop scheduling problem (FJSP).
  • An improved multi-objective imperialist competitive algorithm (IMOICA) was developed, incorporating non-dominant sorting.
  • Key algorithmic enhancements include social hierarchy initialization, attraction-repulsion (AR) for assimilation, revolution strategy for diversity, and variable neighborhood search (VNS) for exploitation.

Main Results:

  • The proposed IMOICA demonstrates efficiency in solving the surgical case scheduling problem.
  • Experiments indicate that advance scheduling leads to significant savings in both time and cost.
  • The algorithm effectively optimizes scheduling by considering patient-specific preparation and switching times.

Conclusions:

  • The developed IMOICA is a viable and efficient tool for optimizing surgical case scheduling.
  • Proactive scheduling through advanced algorithms can lead to substantial operational efficiencies in healthcare.
  • This approach offers a robust solution for complex resource allocation challenges in surgical departments.