Research On Joint Replenishment Promblem Based On Fuzzy Simulation

Joint replenishment problem is to determine the order batch size andordering cycle of each product in a multi-product inventory replenishmentproblem, so as to minimize the total cost during unit time on the basis of meetingcertain needs.In the traditional joint replenishment model, the researchersassumed that quality is good and demands are constant, and then identified theorder batch and ordering cycle.But in the real life,because the demands and costsare affected the market environment and external factors, and the products areperishable,unpredictable fluctuations are possible, the exact value is not inferredbased on the historical data,uncertain factors appear in the joint replenishmentproblem,because of that,the external or internal reasons which caused theuncertain factors can not be ignored on the study of the joint replenishmentproblem.Firstly,this paper studied the joint replenishment model in which thedemands and resource constraint condition are both fuzzy variables,and fuzzyvariables were described by trapezoidal or triangle fuzzy numbers,and the fuzzyset theory was also be introduced in this paper,and the fuzzy expected valuemodel was established in the joint replenishment problem,the objective functionis to minimize the total cost of the product.A genetic algorithms combined withfuzzy simulation technology, the hybrid intelligent algorithm was used to solvethe problem,the fuzzy expected value model and algorithm were put forward inthis paper,and the solution results which were transformed into the clear modelcombined with Silver algorithm were compared,at last,the effectiveness of thealgorithm are verified through the numerical examples.Secondly,this paper also studies joint replenishment problem under the fuzzymulti-resource constraints,the extension of the joint replenishment problem weregiven,building a fuzzy constraints joint replenishment problem model,fund and storage space is described by triangular fuzzy numbers,and genetic algorithmwhich was more classic of the optimization algorithm has been used to solve themodel,and in the end of the paper,the examples are given to verify theeffectiveness of the algorithm.Finally,the model and algorithm have been applied in the inventorymanagement system which was designed to verify the feasibility of the algorithm.