Stochastic Inventory Policies For Reverse Logistics

The highly uncertainty of return products in quantity, time and quality, as well as there are several alternative supply sources, making the reverse logistics inventory management difficult and complex. Signed in the limitations of quantitative research in traditional inventory optimization problem, this dissertation uses the Markov Decision Process (MDP) theory to analyze the dynamic nature of the reverse logistics inventory system and optimal inventory policy.Based on morphological changes in the product recovery, the dissertation proposes two kinds of the basic type of reverse logistics inventory systems:directly reuse, remanufacture. On the basis, the dissertation will extend stochastic inventory optimization to the return product life cycle.First, the dissertation studies the reverse logistics inventory system with return product directly reuse, in which only one inventory point, assuming that demand and return are independent of each other, without disposal of return product. For the unit demand and return, the dissertation construts one-dimensional continuous-time Markov model to prove that the inventory cost function has exactly the same structure as inventory cost function of the traditional inventory model with (s, Q) inventory policy. Then, subject to the general random distribution for demand and return, the dissertation proves the inventory level of the reverse logistics inventory system can be broken down into two parts, the dynamic characteristics of part is the same as the traditional inventory system, the other part is independently the external order, so the optimal inventory policy of reverse logistics inventory system is (s, S) inventory policy.Because of reverse logistics inventory models can be converted into forward logistics inventory model with (s, S) inventory policy under certain conditions, some traditional inventory optimization algorithms can also be used in the reverse logistics inventory system. The dissertation investigates different recovery parameters affecting the average inventory cost by linear search method proposed by Zheng&Federgruen three areas of demand rate, return rate and product retrun process. The numerical results show that, if we adopt a reasonable inventory control policy, return rate is fairly limited impact on the average inventory cost. Only when return rate is very high, it is necessity to disposal return product in order to avoid excessive inventory levels. At the same time, the dissertation pointed out to control the product return information by means of prediction and monitoring that can reduce the average inventory cost of reverse logistics inventory system.Second, the dissertation studies the reverse logistics inventory system with return product remanufacture, which has two inventory point of recovery inventory and serviceable inventory. The dissertation assumes that demand and return are independent of each other, without disposal of return product. The dissertation consideres a hybrid production and remanufacturing system where both production and remanufacturing operations are performed by the same single server, and remanufacturing operation has priority. This dissertation construtes the inventory model by Markov Decision Process (MDP), which uses the coefficient of uniformization to discretization, so the optimality equation is derived. This dissertation firstly studies the structure of optimal inventory policy in the discount cost situatio, then proves that the optimal inventory policy is the inventory policy that based on the optimal initial inventory level of serviceable inventory in the average cost situatio.For the optimal average inventory cost, the dissertation constructs two-dimensional continuous-time Markov chain truncated model, and proposes a solution algorithm based on matrix-geometric methods to solve steady-state probability. In order to improve computational efficiency, the dissertation proposes three heuristic algorithms for solving the approximation of the optimal initial inventory level, in which heuristic1,2are based on the precise formula of the production queuing system with product return, heuristic3is a combination of both. Numerical studies have shown that in most cases, especially in the shortage cost is not very high, all three heuristics can obtain the good approximate value. Heuristics2may reduce approximately77%computing time to obtain the optimal inventory cost than the complete enumeration method. Finally, the dissertation compares the computing time performance of three algorithms for solving steady-state probability. Numerical experiments show that the matrix geometric algorithm proposed by the dissertation has the fastest average speed.Once again, on the basis of the above studies, the dissertation discusses optimal inventory policy of reverse logistics inventory system in the various stages of the return product life cycle. The dissertation uses the demand rate and the returns-ratio different combination to represent the specific stage of the return product life cycle, establishes a Markov inventory model, carries on the value experiment to find the optimal inventory policy on a variety of possible inventory policies. The results indicate that the optimal inventory policy structures to be used over the return product life cycle depend on the holding cost structure of the system. The optimal parameter values of the inventory policies are sensitive to the changes in demand rate and return rate, and the cost of an inventory policy is sensitive to the changes in its parameters values. Hence, it is recommended to revise the inventory policies over the return product life cycle every time a change in demand rate and/or return rates occurs. Instead of frequently revising the inventory policies over the life cycle, if no revision or only a partial revision is done, then a significant amount of additional cost occurs. The optimal inventory policies based on the MDP model are also good approximations of the optimal policies in a finite-horizon life cycle setting if the life cycle stages are at least a few periods long. Clearly, as the number of periods in which a certain pair of demand rate and return rate is valid increases, the performance of the optimal inventory policy improves.Finally, the dissertation summarizes the study results of the stochastic inventory optimization problem in reverse logistics, and discusses some assumptions in the course of the study, proposes the extension directiones for further research. The dissertation contains28figures,23table and169references.