| Supply chain configuration is refer to further optimization of supply chain by choosing best strategies from alternative procurement, production, distribution or other strategies and setting optimal multi-level inventory control policy parameters from the perspective of system global optimization. Using this ways to ensure strategy, planning and operations strategies for supply chain management can be dynamic adjusted based on market environment and ultimately to obtian the overall coordination and optimization of supply chain. With increasing uncertainty of market demand and growing populations of medium, small or micro-enterprises, traditional discrete manufacturing’s supply chains show a high complexity and dynamic nature, meanwhile, supply capacity increasingly constrained by capacity constraints of medium, small or micro-enterprises. In the study of supply chain configuration problems, optimization for alternative strategies selection and inventory control parameters setting considering demand uncertainty and capacity constraints is will become increasingly important and urgent. Using a most common multi-echelon inventory system modeling approach (guaranteed service model), we studied the discrete manufacturing supply chain optimization configuration under demand uncertainty and capacity Constraints.Firstly, we explained the practical and theoretical value of this dissertation from the research progress in supply chain configuration and guaranteed service model combined supply chain management problems in discrete manufacturing. With integration of strategic management of supply chain, we put forward a supply chain configuration application solutions, this work offers possibility for dynamic adjustment of supply chain strategy, planning and operational strategies.Secondly, we establish a supply chain configuration model for capacity constraints. Based on the guarateed service model undel capacity constraints, we establish the supply chain configuration model for common procurement, assembly, distribution stage.Finally, we propose an improved genetic algorithm with high accuracy to solve this model. In this algorithm, we redesign the chromosome initialization rules and genetic operators for large-scale, complex supply chain network. Contrasting with a exact algorithm, we get the solving accuracy. Through sensitivity analysis of uncertainties in demand-side and capacity in supply-side, we derived some insights about supply chain configuration.In this dissertation, the established mathematical model for supply chain configuration problems under market demand uncertainty and capacity constraints and proposed improved genetic algorithm can be made up for the lack of theoretical research in existing supply chain configuration. Meanwhile, the results in the experimental simulation in this dissertation provide feasible advices for alternative strategies selection and guaranteed service time setting. |
