A novel simulated metamorphosis algorithm for homecare nurse scheduling

M. Mutingi, C. Mbohwa

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

Abstract

Inspired by the biological concepts of metamorphosis evolution, this paper presents a novel simulated metamorphosis (SM) algorithm for solving the homecare nurse scheduling problem in a fuzzy environment. The algorithm is motivated by the need for interactive, multi-objective, and efficient optimization approaches to solving problems with fuzzy conflicting goals and constraints. The SM goes through initialization, growth, and maturation phases, mimicking the metamorphosis process. Initialization generates a candidate solution which successively goes through growth and maturation loops. Comparative computational tests on benchmark problems show that, when compared to other algorithms, SM is more efficient and effective, producing near-optimal solutions within reasonable computation times.

Original languageEnglish
Title of host publicationIEEM 2014 - 2014 IEEE International Conference on Industrial Engineering and Engineering Management
PublisherIEEE Computer Society
Pages345-349
Number of pages5
ISBN (Electronic)9781479964109
DOIs
Publication statusPublished - 2014
Event2014 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2014 - Selangor, Malaysia
Duration: 9 Dec 201412 Dec 2014

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
Volume2015-January
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Conference

Conference2014 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2014
Country/TerritoryMalaysia
CitySelangor
Period9/12/1412/12/14

Keywords

  • Simulated Metamorphosis
  • fuzzy evaluation
  • home healthcare
  • nurse scheduling

ASJC Scopus subject areas

  • Business, Management and Accounting (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

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