Modeling for Random Inventory System Based on Monte Carlo Theory and Its Simulation

Abstract

A reasonable strategy is the key to control stocks in the random inventory system. Yet it is difficulty to design such strategy by analytical method because of the randomness of variables and complex and nonlinear relationship among them. This paper provides a random inventory model with no filling the missing. The model generates the random variables subjected to the distribution of requirement and arrival delay firstly based on Monte Carlo theory, and then utilizes the strategy of (s, S) to change the lower and upper order points, and takes the ordering point and ordering quantities as input variables, the total inventory costs as output variables. By simulation with computer and exhaustive method, it seeks the global optimal strategy. Simulation method presented in the paper avoids the affects of the randomness of variables, which is an effective method to solve random system problems.

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