Multi-Objective Simulation-Based Optimization for Effective Management of the Outpatient Chemotherapy Process

Majed Hadid*, Adel Elomri*, Oualid Jouini, Laoucine Kerbache*, Ahmed Saleh, Anas Hamad

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

Outpatient chemotherapy departments' operational harmony depends on the proper strategic, tactical, and operational decisions. The integrated consideration of capacity dimensioning, resources planning, scheduling policy, appointment planning, scheduling, and resources-to-patients assignment can improve the outpatient chemotherapy process's (OCP) overall performance due to interdependencies. However, developing a comprehensive and stochastic OCP decision support system is complex. Thus, the planning, scheduling, and assignment problems are rarely addressed together. Therefrom, a multi-objective simulation-based optimization approach is proposed in this paper to handle the various OCP challenges. The proposed approach showed superior performance compared to a baseline using real data from an outpatient chemotherapy center.

Original languageEnglish
Pages (from-to)1639-1644
Number of pages6
JournalIFAC-PapersOnLine
Volume55
Issue number10
DOIs
Publication statusPublished - 2022
Event10th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2022 - Nantes, France
Duration: 22 Jun 202224 Jun 2022

Keywords

  • artificial intelligence
  • blackbox optimization
  • cancer
  • decision making heuristic
  • multi objectives
  • oncology health care
  • outpatient chemotherapy
  • planning
  • scheduling
  • stochastic simulation based optimization

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