Fuzzy Multi-Criteria Simulated Evolution for Nurse Re-rostering

Michael Mutingi, Charles Mbohwa

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In a fuzzy environment where the decision making involves multiple criteria, fuzzy multi-criteria decision making approaches are a viable option. The nurse re-rostering problem is a typical complex problem situation, where scheduling decisions should consider fuzzy human preferences, such as nurse preferences, decision maker's choices, and patient expectations. For effective nurse schedules, fuzzy theoretic evaluation approaches have to be used to incorporate the fuzzy human preferences and choices. The present study seeks to develop a fuzzy multi-criteria simulated evolution approach for the nurse re-rostering problem. Experimental results show that the fuzzy multi-criteria approach has a potential to solve large scale problems within reasonable computation times.

Original languageEnglish
Title of host publication6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016
PublisherIEOM Society
Pages2025-2033
Number of pages9
ISBN (Print)9780985549749
Publication statusPublished - 2016
Event6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016 - Kuala Lumpur, Malaysia
Duration: 8 Mar 201610 Mar 2016

Publication series

NameProceedings of the International Conference on Industrial Engineering and Operations Management
Volume8-10 March 2016
ISSN (Electronic)2169-8767

Conference

Conference6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016
Country/TerritoryMalaysia
CityKuala Lumpur
Period8/03/1610/03/16

Keywords

  • Fuzzy simulated evolution
  • Fuzzy theory
  • Multiple criteria
  • Nurse re-rostering

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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