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Meta-heuristics for dynamic real time scheduling of diffusion furnace in semiconductor manufacturing industry

Author

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  • M. Vimala Rani
  • M. Mathirajan

Abstract

Most of the earlier research in dynamic scheduling (DS) of diffusion furnace (DF), considers only future arrival of jobs. However, in reality along with the future arrival of jobs, various unexpected real time events (RTE) related to jobs, and/or resources will occur. Hence, this study addresses the important real life characteristics of both future arrival jobs and the occurrence of a RTE while scheduling DF, called as dynamic real time scheduling (DRTS), with the scheduling objective of minimising total weighted tardiness (TWT). This study first explains the mathematical model for DS of single DF to minimise TWT. Then, this study proposes 12 variants of meta-heuristics (six variants of simulated annealing and six variants of tabu search) by considering six different initial solutions obtained from six variants of greedy heuristic algorithm for DRTS of DF. From empirical and statistical analyses on 270 problem instances, this study observed that one of the variants of simulated annealing consistently performing better.

Suggested Citation

  • M. Vimala Rani & M. Mathirajan, 2020. "Meta-heuristics for dynamic real time scheduling of diffusion furnace in semiconductor manufacturing industry," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 34(3), pages 365-395.
    • Handle: RePEc:ids:ijisen:v:34:y:2020:i:3:p:365-395
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