Integrated safety stock optimization for multiple sourced stockpoints facing variable demand and lead time

Abstract

The safety stock placement problem of a multi-stage supply chain comprising multiple sourced stockpoints is addressed in this paper. Each stockpoint faces variability in its downstream demand and suppliers' lead time. The maximum among these suppliers' lead time is determined by employing concepts of order statistics. It is required to find the fill rate and safety stocks at each stockpoint that leads to satisfying the end customer service level at minimum safety stock placement cost. Hence, the fill rates and the safety amounts are decided from a global supply chain perspective. Two models are proposed; a decentralized safety stock placement model and a centralized consolidation model. The decentralized model finds the safety amounts at each stockpoint required to face its underlying lead time demand variability. The consolidation model finds the consolidated safety amounts that will be kept in the relevant consolidation center at each stage. A Benders decomposition technique is developed to handle the nonlinearity and binary restrictions involved in the safety stock consolidation model. Strategies proposed by the consolidation model achieve 45.2–62% reduction in safety amounts that results in a cost savings ranging between 22.2–44.2% as compared to the strategies proposed by the decentralized model. ► Safety stock placement problem of multi-stage supply chains is investigated. ► Stockpoints undergo variability of customer demand and multiple suppliers lead time. ► Two models representing the centralized and decentralized policies are proposed. ► The centralization model is solved efficiently using Benders decomposition technique. ► 22.2–44.2% reduction in cost is achieved by the centralization policy.