In this paper, an extremely short shelf-life inventory of age-discriminated stochastic demand is considered. Age discriminated demand can be found in products of high circulation and short shelf-lives such as dairy products, packaged food, pharmaceutical products and medical products of short shelf lives. Simulation based optimization is considered to find the optimal order quantity. The model employs Discrete Event Simulation along with a modified simulated annealing algorithm. To validate the model and the optimization algorithm, the classical newsvendor problem is tested first, later, different experiments are carried out for different product lifetimes. In contrast to the classical newsvendor, this problem tackles a multi-period inventory of different ages and different demand distributions. The objective is to determine the optimal order quantity to satisfy the stochastic demand of all ages such that shortages and expirations are minimized. The results showed remarkable performance and outstanding minimum levels of shortage and expiration.