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Proceedings of 2012 3rd International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012) pp 117–125Cite as

Study on an Affected Operations Rescheduling Method Responding to Stochastic Disturbances

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Abstract

Literature on job shop scheduling has primarily focused on the development of predictive schedules in static environment. However, when the schedule is carried out in job shop, it may affected by varied disturbances. These disturbances will make the original schedule worse, even invalid. Rescheduling is the process of finding a new schedule to respond to the stochastic disturbances. In this paper, an affected operations rescheduling method (AORM) is studied to respond to disturbances. First, the basic theory of the method is given. Then the algorithmic procedure is introduced. The objective functions evaluating the rescheduling method are given. At last, an illustration example is tested and analyzed. The result shows that the rescheduling method proposed can produce new optimal schedules to respond to stochastic disturbances.

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Acknowledgement

This research was partially supported by the National Science Foundation of China (70371040), Shanghai Leading Academic Discipline Project (B602) and the Fundamental Research Funds for the Central Universities.

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Authors and Affiliations

  1. College of Mechanical Engineering, Donghua University, Shanghai, China

    Ya-qin Zhou, Bei-zhi Li, Jian-guo Yang & Peng Yang

Authors
  1. Ya-qin Zhou
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  2. Bei-zhi Li
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  3. Jian-guo Yang
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  4. Peng Yang
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Corresponding author

Correspondence to Ya-qin Zhou .

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Editors and Affiliations

  1. , College of Management and Economics, Tianjin University, Tianjin, 300072, China, People's Republic

    Runliang Dou

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Zhou, Yq., Li, Bz., Yang, Jg., Yang, P. (2013). Study on an Affected Operations Rescheduling Method Responding to Stochastic Disturbances. In: Dou, R. (eds) Proceedings of 2012 3rd International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33012-4_13

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