Paper Title
Optimal Lot Size Under Uncertain Supply, Stochastic Demand And Cycle Service Level

We consider a retailer who is facing uncertain supply as well as demand and who has to make a stocking decision for a given selling period. If demand exceeds supply, the unmet demand is lost and if the opposite happens, any units left can be salvaged at a reduce value. When demand is unmet, there is lost goodwill as well as the risk of loss of future business. In literature this problem is considered a variant of newsvendor problem. Retailers prefer using service level rather than the shortage penalty to determine the tradeoff between revenue and the loss of goodwill or loss of future business. In this paper, we develop a procedure for finding the optimal policy for the retailer assuming general distributions for the yield as well as demand. The goal is to maximize expected revenue given the cycle service level. The results have important implications for a retailer when a portion of the inventory may be lost due to variety of factors including failure to meet quality standards, theft or perishability. Keywords- Data Mining, Intelligent Systems, Financial Risk, Early Warning.