Stochastic Multi-Period IRP And LRIP For Perishable Items

As the science and technology advanced and standard of people's living improved, the demand of consumers to diversification and individuation of products has increased, some daily necessities such as fresh fruits, vegetables, various meat, mobile phones, computers, clothes and so on tend to diversification. This type of products has a short market life cycle. And they are easily perishable. Just like raw and fresh products, the loss ratio has raised to 20 percent in the process of production, storage, transportation and consumption. Especially, this situation is more serious in urban. Consequently, how to optimize the logistics distribution system efficiently and scientifically is the key point in keeping the stability, reliability of the perishable goods distribution system.The perishable logistics system basically consists of suppliers, distribution centers and demand points (customers).The total operation cost mainly includes third parts:inventory holding cost, shipment cost and construction cost. However, the published Literatures in the field of optimization of perishable logistics, location-allocation problem (LAP), vehicle-routing problem (VRP) and inventory control problem were solved separately. In fact, there was a close relationship among inventory control, facilities location and vehicle routing arrangement. Therefore, it is necessary to make a further study on the internal relationship among these three problems.In this thesis, relevant results of IRP and LRIP in the literature were discussed with the background of perishable distribution problem. Additionally, we respectively focus on stochastic IRP and LRIP in the perishable distribution system by briefly summarizing and analyzing such system.Firstly, the thesis investigates a stochastic multi-item IRP in perishable distribution system. Considering their perishable characteristics, using periodicity replenishment strategy, and referencing inventory control model based on time in VMI, We propose a stochastic multi-item model for IRP. The object is to minimize the total cost including order cost, storage cost, loss cost, expired cost, transportation cost and so on. A mixed genetic algorithm in which embraced with a C-W algorithm had been used in section 3. Through numerical results we verify the feasibility of our model and algorithm.Secondly, we study a stochastic LRIP in perishable distribution system. Adding distribution center's construction cost and satisfying some certain constraints such as vehicle capacity limited, each retailer inventory capacity limited so on. We propose a stochastic model for LRIP. The object is to minimize the total cost including distribution center's construction cost, distribution center's inventory cost and transportation cost.And then, a two-stage heuristic algorithm for solving the problem is conducted, and we illustrate the model and algorithm by employing a numerical study.At last, a brief summary of the thesis is developed to point out the limitations and extending directions of the research.