Simulation Based Optimization Approaches For Multi-echelon Inventory Control Of Supply Chain Distribution Networks

Under the mode of the supply chain management, the inventory is always the biggest obstacle. The inventory not only influences the integrated cost of a single enterprise, but also restricts the performance of the whole supply chain. The past single enterprise inventory management approach already can not adapt the request of the supply chain management. In recent years, the control and optimization of the multi-echelon inventory in the supply chain distribution networks has become one of the focus problems in the supply chain management.The complexity of the multi-echelon inventory control problem lies in that all the node enterprises of the echelons are the inventory holders. The analytical approach can not solve the complex problem of the multi-echelon inventory system in the supply chain effectively because the multi-echelon inventory problem is influenced by uncertainties and the complexity of it is much higher than the single node inventory problem. The simulation approach can process the uncertainty and complexity problem effectively compared with the analytical approach, thus the simulation approach plays a more and more important role in the study of the supply chain. However, the simulation approach is not an optimization approach and it can not provide the optimal solution or the satisfactory solution of the problem. So the simulation is combined with the optimization to form the simulation-based optimization (SBO) approach, which can achieve the system optimization in a real sense.In this dissertation, we discuss the multi-inventory system of the supply chain distribution network. The discrete event simulation model of this system is built and SBO is applied to solve the basic multi-echelon inventory control optimization problem, the multi-echelon inventory control optimization problem with time-varying price, the multi-echelon inventory control combined with pricing optimization problem with phase-varying price and the emergency inventory control optimization problem in the disruptions. On the basis, the distribution center location allocation problem is studied by SBO with the case-based reasoning (CBR). The major work of this dissertation focuses on six sections as follows:(1) We survey the current researches on both the multi-echelon inventory control and optimization problem of the supply chain distribution network and the SBO approach. First, we divide the research approaches on the multi-echelon inventory control problem into four development phases, which are the mathematical programming approach, the intelligent optimization approach, the simulation approach and the SBO approach. The representative research results in the four phases are outlined. Second, the theory of SBO is introduced. According to the function of the simulation, SBO is divided into three aspects: demonstrating the strategies, getting the evaluation for the optimization and getting stochastic parameters or functions by simulation. Last, we survey researches on the applications of SBO in the complex project system, the supply chain and logistics system, the manufacturing system and the society economics system.(2) The multi-echelon network stochastic inventory control problem is researched. Its discrete event system simulation model is built with the practical complex factors, which are the customer arrival time following the Possion distribution, the stochastic customer demand, the stochastic customer purchase behavior, the stochastic ordering time and the manufacture's production limit. The simulation model is implemented on the computer through the object-oriented technique. The simulation-based Particle Swarm Optimization (PSO) approach is applied to solve the problem. The feasibility and the effectiveness of the simulation-based PSO approach are demonstrated by comparing with the E.O.Q. approach.(3) The multi-echelon inventory control problem with time-varying price is researched. The real-time updating inventory control strategy is proposed for the multi-echelon inventory control problem with the time-varying price and the demand fluctuation. The simulation experiment shows that the real-time updating inventory control strategy has a good effect on the inventory problems with different time-varying prices.(4) The combined multi-echelon inventory and pricing problem is researched. Taking into account the demand influenced by the phase-varying price, the adjustment lead time method is proposed for the combined multi-echelon inventory and pricing problem. Based on the simulation model, SBO is applied to solve the problem and the decision variables include the phase prices, the phase adjustment lead times and the phase inventory control strategies. The simulation experiment demonstrates that the proposed multi-echelon inventory control combined with pricing strategy is very effective for increasing the total profit of the supply chain.(5) The emergency inventory control problem in disruptions is researched. SBO is applied to solve the problem that how the supply chain makes the emergency inventory control strategies under the circumstance that the distribution centers are disrupted. The simulation experiment shows the proposed emergency strategies are very effective to reduce the loss of the supply chain and the reference emergency strategies are provided for the supply chain managers. (6) The distribution center location allocation problem of the multi-echelon inventory system is researched. This problem includes two sub-problems, which are the distribution center location problem and the goods allocation problem. The Genetic Algorithm (GA) is nested by PSO and SBO with CBR is applied to solve the problem. The structure and parameters of the distribution network are optimized. Meanwhile the computing time is saved and the efficiency of SBO is promoted.