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

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.     

Lead time reduction strategies in a single-vendor-single-buyer integrated inventory model with lot size-dependent lead times and stochastic demand

This paper studies alternative methods for reducing lead time and their impact on the safety stock and the expected total costs of a (Q,s) continuous review inventory control system. We focus on a single-vendor-single-buyer integrated inventory model with stochastic demand and variable, lot size-dependent lead time and assume that lead time consists of production and setup and transportation time. As a consequence, lead time may be reduced by crashing setup and transportation time, by increasing the production rate, or by reducing the lot size. We illustrate the benefits of reducing lead time in numerical examples and show that lead time reduction is especially beneficial in case of high demand uncertainty. Further, our studies indicate that a mixture of setup time and production time reduction is appropriate to lower expected total costs.     

Design of a novel adaptive inventory control system based on the online identification of lead time

In this paper, an adaptation method for the online identification of lead time is incorporated in production–inventory control systems. Based on the lead time estimate, the tuning parameters are updated in real time to improve the efficiency of the system. Combination of the adaptive scheme with a proportional control law is able to eliminate the inventory drift that appears when the actual lead time is not known in advance or when it varies with time. A detailed analysis is provided for the proposed production–inventory system, including a stability analysis and the quantification of its bullwhip effect. Several examples and comparison with state-of-the-art alternative approaches illustrate the efficiency of the system.