Mathematical Modeling for Gastronomy Service Process

  • Takashi TanizakiEmail author


This section describes a design method using operations research, especially simulation and mathematical optimization, for a gastronomy service system. Operations research is a study that provides an optimal operation method to a system. Operations research includes various methods such as linear programming, combinatorial optimization, queuing, and simulation. Therefore, it is necessary to use a suitable method for system characteristics and the design purpose.


  1. J.L. Heskett, W. E. Sasser, Jr., L.A. Schlesinger, The service profit chain, Simon & Schuster Inc., NY (1997)Google Scholar
  2. Y. Katoh, T. Mitsunari, H. Tsukiyama, Cellular Automaton, Morikita Publishing Co. Ltd., p. 17 (1998)Google Scholar
  3. H. Kawamura, H. Kurumatani, A. Ohuchi, A Study on Coordination Scheduling Algorithm for Theme Park Problem with Multiagent. Technical Report of IEICE 102(613), 25–30 (2003)Google Scholar
  4. T. Murakami, T. Arai, Invitation to Serviseology Service Innovation by Value Co-creation, p. 188, University of Tokyo Press (2017)Google Scholar
  5. H. Nakanishi, S. Koizumi, H. Ishiguro, T. Ishida, Toward Public Simulation of Emergency Escape. Transactions of the Japanese Society for Artificial Intelligence 18(6), 643–648 (2003)Google Scholar
  6. F. Nobutada, O. Junpei, Toshiya, K., Takeshi, S., A Study of Co-creative Staff Shift Planning Method in Food and Drink Industry”, Proceedings of Third Domestic Conference for Serviceology, pp. 294–298 (2015)Google Scholar
  7. F. Ohi, M. Onogi, A Simulation of Evacuation Dynamics of Pedestrians in case of Emergency by Two-dimensional Cellular Automation Method. Transactions of the Operations Research Society of Japan 51, 94–111 (2008)CrossRefGoogle Scholar
  8. Y. Takahashi, H. Morimura, Congestion and Waiting, Asakura Publishing Co. Ltd., pp. 134–115 (2001)Google Scholar
  9. T. Tanizaki, T. Shimmura, Modeling and analysis method of restaurant service process. Procedia CIRP 62, 84–89 (2017)CrossRefGoogle Scholar
  10. T. Tanizaki, T. Shimmura, T., N. Fujii, Shift Scheduling to Improve Customer Satisfaction, Employee Satisfaction and Management Satisfaction in Service Workplace where Employees and Robots Collaborate, Serviceolgy for Services, pp. 15–25(2017)Google Scholar
  11. K. Ueda, K. Markus, A. Monostri, L. Kals, H.J.J. Arai, T., Emergent synthesis methodology for manufacturing, CIRP Annals – Manufacturing Technology, 50(2), 535–551 (2001)Google Scholar
  12. K. Ueda, T. Takenaka, J. Vancza, L. Monostori, Value creation and decision making in sustainable society, CIRP Annals – Manufacturing Technology, 58(2), 681–700 (2009)Google Scholar
  13. I.O. Ugboro, K. Obeng, Top management leadership, employee empowerment, job satisfaction, and customer satisfaction in TQM organizations: An empirical study. J. Qual. Manage. 5(2), 247–272 (2000)CrossRefGoogle Scholar
  14. M. Yagiura, T. Ibaraki, Combinational Optimization, Asakura Publishing Co. Ltd., pp. 1–2 (2001)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Kindai UniversityHigashi- HiroshimaJapan

Personalised recommendations