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Developing a Joint Economic Lot Sizing (JELS) Model in Multi-Stage Supply Chains

Sheikh Sajadieh, Mohsen | 2009

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 39975 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Akbari Jokar, Mohammad Reza
  7. Abstract:
  8. In this thesis, we develop seven integrated production-inventory models for two or three-stage supply chains under stochastic and/or dependent parameters. The problem is called Joint Economic Lot Sizing (JELS) and can be considered as the building block for wider supply chain systems. The first and the second researches deal with the problem in which the supply lead time between the vendor and the buyer is stochastic with uniform and exponential distribution, respectively. The numerical analyses shows that the cooperation between two partners is more critical in unpredictable purchasing environments in terms of stochastic lead-times. In the third research, we investigate four sourcing models with respect to, on one hand, cooperative or non-cooperative planning strategies, and on the other hand, sole or dual sourcing. A two-stage supply chain is considered, which includes a single buyer and either a single or dual vendor(s). Although our study shows that there is no dominating scenario, our models suggest that companies select a single supplier/vendor strategy for their product, and then establish a close collaboration with that vendor. We then developed an integrated model for a three-stage supply chain involving multiple suppliers, multiple manufacturers and multiple retailers, where the lead times from the manufacturers to the retailers are stochastic. It deals with the integer-multiplier coordination mechanism in which the cycle time at each stage is an integer multiple of the neighbor downstream stage. Numerical analyses shows that although the coordination between supply chain members is beneficial, there are also some disadvantages especially when considering stochastic lead time, shortage, and transportation costs. In the fifth research, we developed an integrated production-inventory-marketing model to determine the relevant profit-maximizing decision variable values. The proposed model finds the optimal ordering, shipment and pricing policies. We are able to ascertain the optimal decision variable values employing an analytical solution procedure. The numerical evidence suggests that it is more beneficial for the buyer and the vendor to cooperate with each other when the demand is more price sensitive. We also developed an integrated model where the end-customer demand is positively dependent on the amount of items shown in the display area. The numerical analyses shows that it is more valuable for the buyer and the vendor to cooperate in situations when the demand is more stock-dependent. It also shows the effect of double marginalization in this integrated vendor-buyer model. The last research deals with a manufacturer-retailer model for a two-stage supply chain, where the retailer faces a random demand, and the manufacturer faces a random yield, meaning its production rate is stochastic. For this system we first develop a Markov chain model to compute the optimal coordinated decision policy. The numerical results show that the non-coordinated model in which the backlog is immediately cancelled generally performs best, and the increase in total cost compared to the ideal coordinated model is moderate.

  9. Keywords:
  10. Supply Chain Coordination ; Lot Size ; Joint Economic Policy ; Information Sharing ; Supply Chain ; Integrated Production-Inventory Model ; Centralized Coordination ; Profit Sharing in Supply Chain ; Noncostant Parameters

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