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A Dynamic Scheduling Model with Multiple Process Planning Scenarios Using Markov Models

Fathollahi Chimeh, Mahsa | 2019

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 54018 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Haji, Babak
  7. Abstract:
  8. Cloud Manufacturing have been provided the proper context for efficient and effective using from distributed and various sources for agile and fast responsiveness to various customer demands. Product request from customers lead to define the operations in shop-floor levels that must be process by production equipment in shop-floors. The planning and scheduling problem of this activities have been most important challenge for decision makers. Therefore, the development of ways and methods can exploit efficiently from distributed resources and in confront of customer reqirement have been adaptive is most important. In this study an adaptive approach can be considered in terms of assigning the sources to operations that Imposed in according to stochastic demands to the system. The problem studied in this research modeled with using markov chain methodology and optimized with markov decision process. The issue has been solved for a system with two multi-task machine for two scenarios. The results of the research have shown that the optimal policy for the problem under study has been obtained and this policy of optimal allocation follows a threshold policy. Then, based on this threshold and optimal allocation behavior, algorithms are proposed and their performance is analyzed based on the ratio of the service rates of the two machines to each other
  9. Keywords:
  10. Cloud Manufacturing ; Threshold Policy ; Markov Chain ; Optimum Allocation ; Markov Decision Making ; Scheduling with Queue Models ; Cloud Manufacturing Scheduling

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