Application of a genetic algorithm to staff scheduling in retail sector

Saeed Zolfaghari, Vinh Quan, Ahmed El-Bouri, Maryam Khashayardoust

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

A Genetic Algorithm (GA) is developed for the retail staff scheduling problem. The proposed algorithm is implemented and compared with a conventional integer programming branch-and-bound approach. The performance of the algorithm is tested on six real-world problems. A sensitivity analysis is carried out on three problems for two genetic parameters: population size and mutation rate. Using statistical analysis, the effects of these parameters on the solution quality and computational times are studied. The comparative study shows that GA can produce near-optimal solutions for all of the test problems, and for half of them, it is more successful than the branch-and-bound method.

Original languageEnglish
Pages (from-to)20-47
Number of pages28
JournalInternational Journal of Industrial and Systems Engineering
Volume5
Issue number1
DOIs
Publication statusPublished - 2010

Keywords

  • GA
  • Genetic Algorithm
  • Integer programming
  • Labour scheduling
  • Meta-heuristics
  • Service operations management

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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