Research On The Random Storage Management Under The Condition Of Limited Warehouse Capacity

The problem of random storage management is one important branch of random operational research. This paper we studies mostly for the store management problem on the conditions of stochastic commodity delivery time after ordering.The total cost includes the ordering cost, storage cost and back-order loss in the storage management which under the condition of limited warehouse capacity. The random storage management discusses the mathematic model of optimum order point on the minimum total cost.Firstly, the paper introduces the universality expressiveness form and expected value model of stochastic programming in theory, and discusses the essence elements and ordinary models in the inventory theory.Secondly, single commodity storage model with delivery time as continual and discrete random variable are established. These models reflect storage management things under different conditions. The paper advances the Monte Carlo computer simulation method and simulated annealing algorithm for solution of these models. A high-speed heuristic algorithm based on enumeration method is used for the example solution, and the results are good.Thirdly, this paper discusses multi-item storage problem which the delivery time as random variable under the condition of limited warehouse capacity. It establishes the expected value model and gives simulated genetic algorithm. A fast algorithm which aims at the example is designed. The optimum order points of three commodities are solved by the algorithm, and the better effects are obtained.Finally, a model of limited warehouse capacity OOS single-item storage management which makes the distribution as random variable is established. The paper analyses the storage model for strong perishable commodity, and advances the practical applicability of the model.