Two-echelon Supply Chain Games In The Uncertain Environment

This thesis considers a supply chain composed by a manufacturer in the upstream and a retailer in the downstream. It's assumed that the supply chain selling a one period product is operated in a fuzzy environment and a random fuzzy environment, respectively.In the fuzzy environment, the fuzziness is associated with the customer demand and the manufacturing cost. Expected value models, chance-constrained programming models and correspondingα-optimistic,α-pessimistic models are developed to determine the pricing strategies for the retailer and the manufacturer.In the random fuzzy environment, the fuzziness is associated with the manufacturing cost. The customer demand is characterized by the uncertainty combined with both fuzziness and randomness. Expected value models are developed to determine the pricing strategies and batch-size decisions for the retailer and the manufacturer. And a hybrid intelligent algorithm based on particle swarm algorithm, neural network and random fuzzy simulation technique is given to solve the proposed models. Numerical examples are given to illustrate the effectiveness of the proposed supply chain models in different situations. The following conclusion has been drawn: in the uncertain environments, the performance of the centralized supply chain outweighs that of the decentralized one; the dominated company reaps higher profits.