Planning capacity and safety stocks in a serial production–distribution system with multiple products

Abstract

This study jointly optimizes the production capacity and safety stocks in a serial production–distribution system supplying multiple products under a guaranteed service approach (GSA). The network comprises one manufacturer operating multiple workcenters, one warehouse with limited storage capacity, and one retailer. The manufacturer must efficiently allocate capacity to the workcenters under a limited budget, while the warehouse and retailer need to maintain safety stocks to achieve a target service level. For a single workcenter processing a single product, the interaction between the production lead time, storage capacity, inventory costs, and safety stock placement is characterized. When the manufacturer has multiple workcenters, the integrated problem is formulated as a non-convex program and is solved using a nested Lagrangian relaxation heuristic. The algorithm dualizes the storage constraint in the first phase and the budget constraint in the second phase. A simulation study is conducted to assess the value of the integration, and computational experiments demonstrate that the nested Lagrangian relaxation heuristic can identify optimal or near-optimal solutions in reasonable CPU times.