Research On Supply Chain Optimization And Contracts Design In Fuzzy Environments

The dissertation does some research maily on supply chain optimation and contracts design in fuzzy envrionments including vender selection problem in fuzzy environments, multi-firm production game with fuzzy demand and supply chain contract including revenue-sharing contract and its application in assembly systems, and the comparison with one-period contract and long-term contract, respectively. The detailed content are as the followings.A fuzzy expected value model and a fuzzy chance-constrained programming for vendor selection problem are proposed. The two models are able to solve vendor selection problem with fuzzy parameters more thoroughly. A genetic algorithm based on fuzzy simulation is designed to solve the models which is proved to be effective and feasible to solve the proposed numerical examples.Dynamical production game models between two firms more than two firms is studied. The market demand is characterized as a fuzzy variable in game model. The expected Nash equilibrium is defined. The existence of the expected Nash equilibrium is proved too. Finally, numerical examples are given to illustrate the rationality and practicality of the proposed game models.Revenue-sharing contract in a supply chain With two kinds of fuzzy demand: fuzzy linear and fuzzy non-linear function which depend on the retailer's selling price is addressed. Both in the fuzzy liner demand case and the fuzzy non-linear demand , the optimal price and optimal quantity are obtained. The conclude is that the optimal quantity in decentralized decision setting is equal to the one when the demand is fuzzy so-price-elastic.Revenue-sharing contract is applied to the assembly system in supply chain. The dissertation compares the revenue-sharing contract in decentralized setting leaded by the assembler with the centralized setting that all the members in the assembly systems make decision together. Some properties of the contract are analyzed and the practicality is obvious for assembly management in a supply chain with fuzzy demand.The dissertation characterizes the uncertain market demand as fuzzy variable and proposed two contracts : one-period static contract and long-term dynamic contract to coordinate the two members (supplier and retailer) in supply chain. The effectiveness of the two contracts is compared. Conclusion indicates long-term contract increases the profit potential of both the total supply chain and each member in the supply chain.