Finding (s, S) policy for inventory system with partial backlog, uncertain demand and lead time using heuristic search: a case study of pharmaceutical products

In the context of the variability of dynamic customer demand, companies are contemplating strategies to fulfill customer needs while maintaining competitiveness in the industry. Nowadays, organizations place a high emphasis on refining supply and demand forecasting to enhance accuracy. Nonetheless, this study of the supply chain, especially in an extremely complex to optimize (s, S) inventory policy under partial backlog with probability distribution of demand and uncertain lead time using spreadsheet stimulation, cyclic coordinate method, and golden-section search with generating automation spreadsheet in Macro, through a case study of slow-moving, medium-moving, and fast-moving products. The primary objective of this paper is to identify optimal inventory management based on (s, S) inventory policy under partial backlog. Uncertain conditions are considered to minimize the total cost. As exploring the papers on inventory management in many kinds of policies, throughout a long-term perspective, successful implementation of these strategies aids enhances supply chain sustainability and competitiveness. This paper analyzes these issues and provides sharp analysis and practical solutions for the pharmaceutical industry.