Metaheuristics for optimizing safety stock in multi Stage inventory system

Abstract

Managing the right level of inventory is critical in order to achieve the targeted level of customer service, but it also carries significant cost in supply chain. In majority of cases companies define safety stock on the most downstream level, i.e. the finished product level, using different analytical methods. Safety stock on upstream level, however, usually covers only those problems which companies face on that particular level (uncertainty of delivery, issues in production, etc.). This paper looks into optimizing safety stock in a pharmaceutical supply considering the three stages inventory system. The problem is defined as a single criterion mixed integer programming problem. The objective is to minimize the inventory cost while the service level is predetermined. In order to coordinate inventories at all echelons, the variable representing the so-called service time is introduced. Because of the problem dimensions, metaheuristics based on genetic algorithm and simulated annealing are constructed and compared, using real data from a Croatian pharmaceutical company. The computational results are presented evidencing improvements in minimizing inventory costs. Key words: Multi stage inventory system, Inventory cost, Service level, Pharmaceutical industry, Mixed integer programming, Metaheuristics