Research On Scheduling Decision Models And Its Optimization For Agile Supply Chains Of Automotive Manufacturing Industry

Automotive is the machine to change the world, the wheel to promote the social go ahead, the engine to ensure the continuous growth of economy and the propeller of the upgrading of the industrial structure. In the 21st century global competition market, in order to improve the operational efficiency and customer service levels, the automotive industry need to gradually change its production style from the traditional Make-to-Stock to Make-to-Order, and the automobile manufacturing supply chain should try to make the progressive realization of lean and agile. After long time of market competition and coordinating development, supply chain enterprises gradually adopt a variety of coordination policies with benefit and risk sharing, inventory management technologies and information sharing technologies which make the supply chain running in a JIT style. Now, in order to further improve supply chain operation efficiency and achieve supply chain agility, the supply chain needs to make the optimization of production and transportation scheduling on the precise operational data of its members.In this thesis, agile strategies and key support agile techniques are analyzed and discussed for automobile manufacturing supply chain, a supply chain structure framework model is built based on the characteristics of scheduling decisions and morphological analysis of the model is analyzed, and then the modelling and optimization methods of the three types of scheduling decision problems of agile supply chains are studied. Firstly, the static scheduling problem is researched where the supply chain needs to deal with a definite demand. the static scheduling needs to decide all of the parts'production and transportation planning which can ensure the supply chain to meet the demand in time with the lowest operational cost based on the schedulable time, operation parameters and the cost rates of the members. The technoloyies, such as time-slot coding, genetic operators, greedy-sequence decoding, which are designed in this section not only resolve the optimization of static scheduling problem, but also firm the strong groundworks for the following two scheduling problems. Then the dynamic scheduling problem is researched where the supply chain needs to change its old schedule because of the old demand quantity is uncorrect and changed now. In the dynamic scheduling process, the decision agent needs to rebuild the supply chain and its optimal production and transportation planning according to the demand changing quantity and the executive situation of the old schedule. The technologies, such as scheduling split interface, key path analysis and time-slot sets classification, which are designed in this section not only resolve the optimization of dynamic scheduling problem, but also firm a strong groundworks for the urgent scheduling problem.. Finally, the urgent scheduling problem is researched where the supply chain need to rescheduling of its old schedule for supply interruptions. There have two kinds of supply interruption: production breakdown and transportation interruption. A common decision model and its optimization algorithm are built based on the original schedule and its exective status. Also, three experiments are proposed to validate the scheduling problems'models and its optimization algorithms.The primary innovations are as follows:(1) The concept of time slots is promoted and its division procedures are designed. Using time-slot to represent corps'available scheduling period changes a continous scheduling decision problem to a descrete one, reduces the optimization difficulty and increases the scheduling precision at the same time.(2) The structure framework model of supply chain based on scheduling is designed. The structures of actual automotive manufacturing supply chains are various, so to construct a common structure framework model of supply chain based on scheduling decisions characteristics is precondition of supply chains'scheduling optimizatioin.(3) The concept of scheduling split interface is defined and the mathmatic models for all of the time slots are set up which give the basis of sets and calculation for optimizing the agile supply chain schedule. In the processes of the dynamic scheduling and the urgent scheduling, the time slots in the origin scheduling should be processed at different manners according to its status, and the scheduling split interface is the key element of the judgement.(4) The hybrid genetic algorithms integrating Greedy-Sequence Decoding Motheds(GSDM) are schemed out which resolve the three scheduling problems of anutomotive manufacturing agile supply chain efficiently. There are a lot of time and quantity constraints in the scheduling decision mathmatic models, the GSDMs can help the HGAs decode exclusive feasible scheduling solutions from a chromosome which is made up of stochastic time-slot codes sequences, and get the optimal solution quickly.