Controlling distribution inventory systems with shipment consolidation and compound Poisson demand

•Heuristics for controlling one-warehouse-multiple-retailer inventory systems.•Time based shipment consolidation and compound Poisson demand.•Single-item and multi-item methods for backorder cost and fillrate constraint models.•Numerical evaluation against existing exact results show near optimal pe...

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Vydáno v:European journal of operational research Ročník 280; číslo 1; s. 90 - 101
Hlavní autoři: Johansson, Lina, Sonntag, Danja R., Marklund, Johan, Kiesmüller, Gudrun P.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.01.2020
Témata:
Civil Engineering
Compound Poisson demand
Engineering and Technology
Inventory
Multi-echelon
Samhällsbyggnadsteknik
Shipment consolidation
Stochastic
Teknik
Transport Systems and Logistics
Transportteknik och logistik
Shipment consolidation
Stochastic
Multi-echelon
Inventory
Compound Poisson demand
ISSN:0377-2217, 1872-6860, 1872-6860
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Shrnutí:•Heuristics for controlling one-warehouse-multiple-retailer inventory systems.•Time based shipment consolidation and compound Poisson demand.•Single-item and multi-item methods for backorder cost and fillrate constraint models.•Numerical evaluation against existing exact results show near optimal performance.•Practical applicability and impact illustrated using real company data. We consider a one-warehouse-multiple-retailer inventory system where the retailers face stochastic customer demand, modelled as compound Poisson processes. Deliveries from the central warehouse to groups of retailers are consolidated using a time based shipment consolidation policy. This means that replenishment orders have to wait until a vehicle departures, which increases the lead time for the retailers and therefore also the safety stock. Thus, a trade-off exists between expected shipment costs and holding costs. Our aim is to determine the shipment intervals and the required amount of safety stock for each retailer and the warehouse to minimize total cost, both for backorder costs and fill rate constraints. Previous work has focused on exact solutions which are computationally demanding and not applicable for larger real world problems. The focus of our present work is on the development of computationally attractive heuristics that can be applied in practice. A numerical study shows that the proposed heuristics perform well compared to the exact cost minimizing solutions. We also illustrate that the approaches are appropriate for solving real world problems using data from a large European company.
ISSN:0377-2217
1872-6860
1872-6860
DOI:10.1016/j.ejor.2019.06.045