Stochastic joint replenishment problem is the joint order of a group of items with stochastic demand

our purpose is to acquire the least total cost. We analyze the problem using periodic review policy

and present an expected value model

acquiring basic order period

order period and the largest inventory of each item

and under the service level constraints. We propose a hybrid genetic algorithm which combines with a stochastic simulations algorithmic and a genetic algorithmic for solving this model

and it can acquire a near optimal replenishment policy. A numerical example is presented to illustrate the effectiveness of algorithm.