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Multi-Echelon Mixed-loop Supply Chain Network Design under Disruption Conditions

Beheshti, Saeed | 2016

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 49029 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Haji, Rasoul; Haji, Alireza
  7. Abstract:
  8. Fulfilling the demands of customers, used to be the main purpose of Supply Chain Network Designers. Soon after that, the environmental concerns created the concept of Reverse Logistic in order to prevent goods from being scattered in the environment after their disposal. Governmental regulations and people's concerns, forced the factories to gather the created pollutions of the environment. They gradualy confessed the positive impacts of these ruturns on their financials. The flow of forward and reverse logistics establishes a Closed-Loop in which the returning economical circumstances were transferd into original factories. Later, Open-Loops were created. In open-loops the returns have to be transfered to factories other than the initial ones, and then have to be sold in second hand markets. Wheras, The only concept which has not been already covered in the literature is the model in which, no condition in ruturning goods only to the initial or only to the other factories is included. It is studied For the first time in this thesis, which we call them mixed-loop suplly chains. We also consider some different senarios representing natural disasters like earthquake that can encounter network with disruptive conditions. In terms of facing with these catastrophes, we design some pre-determined implementations such as, establishment of emergency warehouses and assessment of the possibility of transshipments in order to protect the network against serious problems. Since the coefficents of our model are not clear and we consider them as fussy triangualr numbers, possibilistic programming approach is used to transform the model into a crisp mixed integer linear programming model by using Me measurement. the problem was solved and the sensitivity analysis was implemented by branch and bound method in CPLEX software for appropiate complexities. Then for large sizes of model, the Meta heuristic Genetic Algorithm in MATLAB software was implemented
  9. Keywords:
  10. Closed Loop System ; Genetic Algorithm ; Disruption ; Supply Chain ; Open Loop System ; Mixed Loop ; Possibilistic Programming

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