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

Marije Noordhoek; Wout Dullaert; David S.W. Lai; Sander de Leeuw

doi:10.1016/j.tre.2018.02.006

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

Marije Noordhoek, Wout Dullaert, David S.W. Lai, Sander de Leeuw

Research output: Contribution to journal › Article › Academic › peer-review

5 Citations (Scopus)

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.

Original language	English
Pages (from-to)	292-311
Number of pages	20
Journal	Transportation Research Part E: Logistics and Transportation Review
Volume	114
DOIs	https://doi.org/10.1016/j.tre.2018.02.006
Publication status	Published - Jun 2018
Externally published	Yes

Keywords

Metaheuristics
Multi-echelon inventory
Scatter search
Service-constrained
Simulation-optimization
Supply chain performance

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10.1016/j.tre.2018.02.006

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title = "A simulation–optimization approach for a service-constrained multi-echelon distribution network",

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.",

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AU - Noordhoek, Marije

AU - Dullaert, Wout

AU - Lai, David S.W.

AU - de Leeuw, Sander

PY - 2018/6

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AB - 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.

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

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Keywords

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