Chain RestaurantWork Scheduling Based on Genetic Algorithm with Fuzzy Logic

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

doi:10.20965/jaciii.2006.p0050

Chain RestaurantWork Scheduling Based on Genetic Algorithm with Fuzzy Logic

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

Institute of Science Tokyo

Research output: Contribution to journal › Article › peer-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 language	English
Pages (from-to)	50-59
Number of pages	10
Journal	Journal of Advanced Computational Intelligence and Intelligent Informatics
Volume	10
Issue number	1
DOIs	https://doi.org/10.20965/jaciii.2006.p0050
Publication status	Published - Jan 2006
Externally published	Yes

Keywords

Work scheduling
fuzzy logic
genetic algorithm

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10.20965/jaciii.2006.p0050

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title = "Chain RestaurantWork Scheduling Based on Genetic Algorithm with Fuzzy Logic",

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.",

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AU - Watanabe, Makoto

AU - Nobuhara, Hajime

AU - Kawamoto, Kazuhiko

AU - Dong, Fangyan

AU - Hirota, Kaoru

N1 - Publisher Copyright: © Fuji Technology Press Ltd.

PY - 2006/1

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N2 - 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.

AB - 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.

KW - Work scheduling

KW - fuzzy logic

KW - genetic algorithm

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JF - Journal of Advanced Computational Intelligence and Intelligent Informatics

IS - 1

ER -

Chain RestaurantWork Scheduling Based on Genetic Algorithm with Fuzzy Logic

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Keywords

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