Some Joint Inventory Policies For Reverse Supply Chain: Models And Optimization

Sustainability and environment protection has become a major issue in our modern society and economy. Many leading companies have effectively utilized reverse supply chains to retrieve their used products from customers.This research focuses on a special reverse supply chain system which includes a single centralized returns center (CRC) and multiple local contact points (LCPs). A special attention is on the joint inventory control and product returns handling policies. In detail, LCPs collect used products from local customers and then delivery them to CRC, CRC handles those returned products to recovery part or whole of them, or to retrieve some material from them.From simple to complex, the joint inventory and policy follows the following 3 steps: (â…°) Each LCP independently decides its delivery with the same delivery batch, (â…±) CRC controls the transportation activities of all the LCPs, (â…²) a "can order policy" is introduced to policy (â…±) to avoid transportation with minor quantities. For each policy described above, the purpose is to minimize the system average cost per unit time.To make us learn the VMI system and can order policy more clearly, Chapter 4 has been interpetted into the above discussion. In Chapeter 4, the can order policy is studied in the framework of VMI, that represents an example of can order policy in the forward supply chain.Noting that some LCP also has some limited ability to recovery some used products and can sell those recovered products in the second hand market, we specially introduce a joint inventory policy for these dual channel LCPs with the purpose of maximizing LCP's profit.Finally, note that there are often existed several local optimal solutions in a multiple parameter optimization problem. Usually, these local solutions are almost no obviously different in the objective value, but vary large in the sensitivities tothe system parameter. Therefore, under the situation that supply chain disruption happens often, it is. reasonable to choose a solution with a relative low sensitivity. Thus, a new decision criteria which based on supply chain disruption is introduce in the last part of this paper to improve the normal criteria.