A Modified Genetic Algorithm to Optimize A Multi-item Inventory System with Random Demands and Stochastic Lead Time

Multi-item inventory systems with stochastic demands and lead time are studied to reduce operation costs and use resources effectively. In order to reach minimal costs in the long run, a (s ,S) model based on stochastic demands and lead time is advanced, A modified genetic algorithm based on minimal gene segment coding, two generations competition and adaptive selection was developed to solve the problem, a M-C statistical testing method was presented to compute adaptive values, which significantly improve warehouse and capital management. The result of the modified genetic algorithm shows that over 7% operation costs is saved compared with the result of random generated