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A Novel Service Composition Model for Sustainable Cloud Supply Chain Using Stochastic Programming Approach

Malekpour, Niloufar | 2019

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 52174 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Fatahi Valilai, Omid
  7. Abstract:
  8. Along with globalization of competition and economy, and development of Internet and Ethernet infrastructures, IoT, artificial intelligence, etc., to modify the impact of changes and volatility, active organizations and product chains have faced with an advanced service-oriented manufacturing model based on complicated networks of operation and logistics service providers. On the other hand, appearing of individualized and customized orders have leaded to more complicated manufacturing procedure and manufacturing industries have been more restricted to satisfy varied demands. In the context of physical products and cyberspace convergence, the novel generation of advanced manufacturing systems, cloud manufacturing has emerged to pave the uneven way for enterprises. Having improved efficiency, developed intelligent and sustainable design, production and services, cloud manufacturing has attracted many of researchers’ attention. The main goal of this research is developing a robust allocation model in cloud manufacturing system in which service compositions with lower operational and logistics cost and higher quality would be selected within a fluctuated condition. Uncertainty has always been a significant challenge for global producers. Moreover, in the era of changes, it is critical to conform to these patterns. Finally, the thesis has presented a numerical example and a robust Genetic algorithm to provide significant results
  9. Keywords:
  10. Cloud-based Supply Chain ; Service Composition ; Cloud Manufacturing ; Services Allocation ; Stochastic Programming ; Genetic Algorithm

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