TY - JOUR
T1 - Reducing unmet demand and spoilage in cut rose logistics
T2 - Modeling and control of fast moving perishable goods
AU - Lin, Xiao
AU - Negenborn, Rudy R.
AU - Duinkerken, Mark B.
AU - Lodewijks, Gabriel
PY - 2018
Y1 - 2018
N2 - Fresh cut flower supply chains are aware of the need for reducing spoilage and increasing customer satisfaction. This paper focuses on a part of the cut rose supply chain, from auction house to several end customers. A new business mode is considered that would allow end customers to subscribe to florists and have a continuous supply of bouquets of roses. To make this business mode feasible, we propose to benefit from real-time information on roses’ remaining vase life. First, a quality-aware modeling technique is applied to describe supply chain events and quality change of cut roses among several supply chain players. Then, a distributed model predictive control strategy is used to make up-to-date decisions for supply chain players according to the latest logistics and quality information. This approach provides a tool for multiple stakeholders to collaboratively plan the logistics activities in a typical cut rose supply chain based on roses’ estimated vase life in real time. The proposed approach is compared with a currently used business mode in simulation experiments. Results illustrate that the new business mode and the planning approach could reduce unmet demand and spoilage in a cut rose supply chain.
AB - Fresh cut flower supply chains are aware of the need for reducing spoilage and increasing customer satisfaction. This paper focuses on a part of the cut rose supply chain, from auction house to several end customers. A new business mode is considered that would allow end customers to subscribe to florists and have a continuous supply of bouquets of roses. To make this business mode feasible, we propose to benefit from real-time information on roses’ remaining vase life. First, a quality-aware modeling technique is applied to describe supply chain events and quality change of cut roses among several supply chain players. Then, a distributed model predictive control strategy is used to make up-to-date decisions for supply chain players according to the latest logistics and quality information. This approach provides a tool for multiple stakeholders to collaboratively plan the logistics activities in a typical cut rose supply chain based on roses’ estimated vase life in real time. The proposed approach is compared with a currently used business mode in simulation experiments. Results illustrate that the new business mode and the planning approach could reduce unmet demand and spoilage in a cut rose supply chain.
UR - http://resolver.tudelft.nl/uuid:edfa3b85-3ecf-4060-b297-88ad975b0fe7
UR - http://www.scopus.com/inward/record.url?scp=85053392885&partnerID=8YFLogxK
U2 - 10.1177/0361198118783901
DO - 10.1177/0361198118783901
M3 - Article
AN - SCOPUS:85053392885
SN - 0361-1981
VL - 2672
SP - 130
EP - 140
JO - Transportation Research Record
JF - Transportation Research Record
IS - 9
ER -