A simulation–optimization approach for a service-constrained multi-echelon distribution network

•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...

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Bibliographic Details
Published in:Transportation research. Part E, Logistics and transportation review Logistics and transportation review, 2018-06, Vol.114, p.292-311
Main Authors: Noordhoek, Marije, Dullaert, Wout, Lai, David S.W., de Leeuw, Sander
Format: Article
Language:English
Subjects:
Metaheuristics
Multi-echelon inventory
Scatter search
Service-constrained
Simulation-optimization
Supply chain performance
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Summary:•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. 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.
ISSN:1366-5545
1878-5794
DOI:10.1016/j.tre.2018.02.006