Chain RestaurantWork Scheduling Based on Genetic Algorithm with Fuzzy Logic

Makoto Watanabe, Hajime Nobuhara, Kazuhiko Kawamoto, Fangyan Dong, Kaoru Hirota

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

A quasi-optimization algorithm to generate chain restaurant work scheduling (WS) is proposed based on a genetic algorithm with fuzzy logic, where the whole weekly chain restaurant WS problem is fuzzily decomposed into 7 daily WS problems and a combined weekly WS problem. The proposed algorithm expresses the requirements of individual members by membership functions in fuzzy logic and finds a nearoptimal solution using the genetic algorithm. Experimental results verified that a 24-hour 7-day schedule for 15 workers at a chain restaurant is produced in 6 minutes using the proposed algorithm implemented with C++ and executed on a PC. A professional expert evaluated WS quality as satisfactory.

Original languageEnglish
Pages (from-to)50-59
Number of pages10
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Volume10
Issue number1
DOIs
Publication statusPublished - Jan 2006
Externally publishedYes

Keywords

  • Work scheduling
  • fuzzy logic
  • genetic algorithm

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