A Study On The Supply Chain Collaboration Models Based On Joint Replenishment Policy

With the globalization of economy development, the establishment of high efficiencysupply chain is becoming more and more necessary between the enterprises. Using jointreplenishment strategy, companies in the supply chain can reduce the annual orderingtimes, get more chance of price discount, and decrease transportation cost. This strategy isan effective way for cost savings. This thesis discussed two supply chain collaborativemodels based on joint replenishment policy and novel algorithms for the models.One key is to find an efficient and effective algorithm that can solve JointReplenishment Problem (JRP) which has been proved to be a typical NP-hard problem.Firstly, according to the difficulties of finding the solutions, a differential evolution (DE)algorithm is analyzed and is suggested as an approach to solve the JRP. Then a modifiedDE algorithm is designed and its performance is tested by three classic testing functions.Secondly, the problem of implementing joint replenishment and channel collaborationpolicy is studied. The enterprises in the supply chain usually make purchasing decisionsindependently and only consider their own interests. This pattern is changed and jointreplenishment policy is implemented between enterprises in the supply chain. So, thewhole supply chain is optimized. Considering the enterprises belong to different interestgroups, a benefit sharing mechanism is designed. Lastly, a delivery schedulingcollaborative decision model based on joint replenishment policy in which a centralwarehouse serves n retailers and its algrithm are studied. Then, the extended model withsuppliers offering quantity discounts is discussed. An algorithm based on AHDE algorithmis proposed. At the same time, a numerical example verifies the validity and superiority ofthe proposed model and algorithm.