Application of Genetic Algorithm in a Program Which Creates a Work Shift Table Using VBA and GAS

DOI
  • Kazuaki Tomida
    Graduate School of Informatics and Engineering, The University of Electro-Communications
  • Sato Hiroyuki
    Graduate School of Informatics and Engineering, The University of Electro-Communications
  • Okuno Tsuyoshi
    Graduate School of Informatics and Engineering, The University of Electro-Communications

Bibliographic Information

Other Title
  • VBAとGASを用いたシフト表自動化アプリの作成とシフト組合せ最適化用の遺伝的アルゴリズムの検討

Abstract

<p>In Japan today, the demand for operational efficiency has increased due to the declining birthrate and aging population. However, many efficiency tools to solve these problems require a special IT environment. Therefore, in this research, we developed an application which automatically creates work shift tables for restaurants using general-purpose tools such as VBA and GAS. Furthermore, we examined the genetic algorithm for optimizing shift scheduling. Our application was developed for a work shift table in a weak for a restaurant in which approximately 30 part-time and full-time workers are involved. We used an evaluation function considering each point for each worker. Our genetic algorithm was designed to maximize the sum of the points of applicable workers, while the dispersion of the sum in the weak would be small. The outputs of our genetic algorithm were compared with the real work shift tables used in the restaurant. The holiday correct rate in the work shift table, which is one of important parameters for the operation of the real restaurant, was found to be as high as 80% in the outputs of our application. The calculation time in our genetic algorithm was less than 1 minute using a common laptop computer. Our application has been successfully utilized in the real restaurant, and favorable comments have been received from the users.</p>

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Details 詳細情報について

  • CRID
    1390009294937758208
  • NII Article ID
    130008141303
  • DOI
    10.11394/tjpnsec.12.88
  • ISSN
    21857385
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
    • KAKEN
  • Abstract License Flag
    Disallowed

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