A simulation–optimization approach for a service-constrained multi-echelon distribution network. (June 2018)

• Record Type: Journal Article
• Authors: Noordhoek, Marije; Dullaert, Wout; Lai, David S.W.; de Leeuw, Sander
• Is Part Of: Transportation research. Volume 114(2018)
• Page Start: 292
• Page End: 311
• Publication Date: 2018-06
• Subjects: Supply chain performance -- Multi-echelon inventory -- Metaheuristics -- Service-constrained -- Simulation-optimization -- Scatter search; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2018.02.006
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: Service-constrained multi-echelon distribution networks with real-life constraints. Deterministic lead times, backordering, periodic ( s, S ) inventory policies. Propose novel Scatter Search based simulation-optimization method. Extensive computational testing on synthetic problem instances and a real-life case. Abstract: Academic research on ( s, S ) inventory policies for multi-echelon distribution networks with deterministic lead times, backordering, and fill rate constraints is limited. Inspired by a real-life Dutch food retail case we develop a simulation-optimization approach to optimize ( s, S ) inventory policies in such a setting. We compare the performance of a Nested Bisection Search (NBS) and a novel Scatter Search (SS) metaheuristic using 1280 instances from literature and we derive managerial implications from a real-life case. Results show that the SS outperforms the NBS on solution quality. Additionally, supply chain costs can be saved by allowing lower fill rates at upstream echelons.