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Study On Models And Algorithms Of Joint Replenishment Inventory Problem

Posted on:2006-03-15Degree:DoctorType:Dissertation
Country:ChinaCandidate:Z J LiangFull Text:PDF
GTID:1116360155955128Subject:Transportation planning and management
Abstract/Summary:PDF Full Text Request
The inventory cost of items occupies much more proportion in the total cost of logistics. Therefore, inventory management is important to the modern enterprise, and it is a significant part of logistics management. Optimizing inventory management can make company agile in the market and keep good customer service as it occupy lower capital than before.Although the research and its extensive research of traditional inventory control theory has made great achievement, but with customer demand changing to multi item and little batch, companies always have much variety of items. Under the background, it is not fit to operating inventory with traditional inventory theory. Joint replenishment inventory can lower the average cost of the inventory, get more chance of discount, and enlarge the ordering item amount which make company more chance of truck load transportation.The article deeply analyze the character, traditional control theory of inventory and the jointly replenished multi-item inventory problem, and compare the model and algorithm of joint replenishment problem. According to the type of customer demand, the article makes the systemic research on the model and algorithm of the joint replenish problem (JRP) by the way of deterministic demand and stochastic demand.It is a simple model for the deterministic joint replenishment problem, but it is a NPC problem and has no polynomial algorithm. An algorithm with good robust is the key for the deterministic JRP which can search better solution in acceptable running time. The article compare the representative algorithm, subtly take it as a combinatorial optimization problem, and put up with a simulated annealing algorithm for the deterministic JRP.And then applying a deduction of Lagrangean relaxation algorithm of the problem and simulated annealing theory, present a more robust mix algorithm for the deterministic JRP.The mix algorithm shorten the state space of the problem, and can find local optimum solution in reasonable calculating time with some sample, and sometimes even can find a global optimum solution.For the stochastic JRP, the stochastic character of customer demand and the order lead time make it hard to be researched and resolved. It's common to take...
Keywords/Search Tags:Logistics, Inventory Management, Joint Replenishment, Deterministic Demand, Stochastic Demand, Heuristic Algorithm
PDF Full Text Request
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