Chain Restaurant Work Scheduling Based on Genetic Algorithm with Fuzzy Logic
Makoto Watanabe, Hajime Nobuhara, Kazuhiko Kawamoto,
Fangyan Dong, and Kaoru Hirota
Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan
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 near-optimal 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.
Fangyan Dong, and Kaoru Hirota, “Chain Restaurant Work Scheduling Based on Genetic Algorithm with Fuzzy Logic,” J. Adv. Comput. Intell. Intell. Inform., Vol.10, No.1, pp. 50-59, 2006.
-  T. Inoue, T. Furuhashi, H. Maeda, and M. Takaba, “A Study on Bacterial Evolutionary Algorithm Engine for Interactive Nurse Scheduling Support System,” Proc. of the 1999 IEEE International Conference on Systems, Man and Cybernetics, Nagoya, Vol.5, pp. 533-537, 2000.
-  L. Jeffrey, and A. Ravindran, “A Multiple Objective Nurse Scheduling Mode,” AIIE Transactions, Vol.13, No.1, pp. 55-60, 1981.
-  D. Thierens, and D. E. Goldberg, “Elitist recombination: an integrated selection-recombination GA,” In Proceedings of ICEC 94, pp. 508-512, 1994.
-  D. Thierens, Selection Schemes, “Elitist Recombination, and Selection Intensity,” Proc. 7th International Conference on Genetic Algorithms, pp. 152-159, 1997.
-  W. Pedrycz, and F. Gomide, “An Introduction to Fuzzy Sets,” The MIT Press, pp. 303-325, 1998.
-  W. Pedrycz, “Genetic algorithms for learning in fuzzy relational structures,” Fuzzy Sets and Systems, Vol.69, pp. 37-52, 1995.
-  http://www.houko.com/index.shtml