A partial modification method for disturbed production schedules by using hybrid genetic algorithm

Tomoya Tanikawa, Yoshitaka Tanimizu

Research output: Contribution to conferencePaper

Abstract

Most of the existing studies about production scheduling aim to find an optimum production schedule before starting production activities. However, unpredictable disruptions may occur in the actual manufacturing environment. Therefore, the disturbed production schedule needs to be modified for the unpredictable disruptions. In our previous studies, a reactive scheduling method has been proposed by using a genetic algorithm in order to modify the disturbed production schedule without stopping production activities. However, the proposed scheduling method significantly changes the initial production schedule in the modification process of the production schedule in order to optimize the production schedule. The significant changes of production schedules may confuse the actual manufacturing environment. In this research, we propose a partial modification approach by extending the reactive scheduling method. A hybrid genetic algorithm is developed to improve the disturbed production schedule without greatly changing the initial production schedule. Computational experiments demonstrate that the new method is superior to the previous method.

Original languageEnglish
Publication statusPublished - 2017 Nov 13
Externally publishedYes
Event9th International Conference on Leading Edge Manufacturing in 21st Century, LEM 2017 - Hiroshima City, Japan
Duration: 2017 Nov 132017 Nov 17

Other

Other9th International Conference on Leading Edge Manufacturing in 21st Century, LEM 2017
CountryJapan
CityHiroshima City
Period17/11/1317/11/17

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Keywords

  • Critical path
  • Hybrid genetic algorithm
  • Partial modification
  • Reactive scheduling

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

Cite this

Tanikawa, T., & Tanimizu, Y. (2017). A partial modification method for disturbed production schedules by using hybrid genetic algorithm. Paper presented at 9th International Conference on Leading Edge Manufacturing in 21st Century, LEM 2017, Hiroshima City, Japan.