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 |
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Pages (from-to) | 292-311 |
Number of pages | 20 |
Journal | Transportation Research Part E: Logistics and Transportation Review |
Volume | 114 |
DOIs | |
Publication status | Published - Jun 2018 |
Externally published | Yes |
Keywords
- Metaheuristics
- Multi-echelon inventory
- Scatter search
- Service-constrained
- Simulation-optimization
- Supply chain performance