Agriculture Reference
In-Depth Information
State of the Art
In a recent special issue in
OR Spectrum
(Grunow and Van der Vorst
2010
), Akker-
man et al. (
2010
) presented a review of the design and management of agri-food
distribution networks. They concluded that the limited shelf lives of food products,
requirements with regard to temperature and humidity, possible interaction effects
between products, time windows for delivering the products, high customer ex-
pectations, variability in supply and demand (e.g. weather dependability), and low
profit margins make distribution management of fresh products a challenging area.
This has only recently begun to receive more attention in the operations manage-
ment literature.
The introduction of unbroken cold chains, an uninterrupted series of storage and dis-
tribution activities which maintain a given temperature range, has improved the quality
of food products at the market place. Quality assurance guidelines and standards such
as Good Manufacturing Practice (GMP) and HACCP (Hazard Analysis and Critical
Control Points) have been developed and implemented in food supply chains (Luning
et al.
2008
,
2009
). Moreover, breeding and cultivation practices have improved in or-
der to increase the initial product quality at harvest. From a logistics point of view, em-
phasis has been on developing management concepts that improve delivery reliability
and lead times. This is accomplished via increased information exchange and changes
of roles in the chain, e.g. Cross Docking, Vendor Managed Inventory (VMI), Efficient
Replenishment, Collaborative Planning Forecasting and Replenishment (CPFR) and
Factory Gate Pricing (FGP). Also innovations in logistic means, such as reefers and
RFID's (radio frequency identification) have been important. It is clear that logistics
improvements go hand in hand with technological developments and quality assurance
systems. However, up to now a complete integrated perspective has not been taken.
Temperature monitoring and recording is a prerequisite for chain control and any
logistics management system that aims on product quality optimization. New tech-
nological developments, such as time-temperature integrators or indicators to indi-
vidually monitor the temperature conditions of food products throughout distribu-
tion, offer possibilities to improve temperature monitoring throughout the distribu-
tion system (Giannakourou and Taoukis
2003
). This allows for shelf life estimation
using quality prediction models, as is for example shown by Tijskens (
2004
) for fruit
and vegetable chains, Raab et al. (
2008
) for pork and poultry chains and Dalgaard
et al. (
2002
) for fish chains. The additional information gained from these technolo-
gies would allow for advanced logistics decision making during the complete distri-
bution process knowing the required product quality at its final destination, a con-
cept called “Quality Controlled Logistics” (Van der Vorst et al.
2007
,
2009
,
2011
).
Quality Controlled Logistics
Fresh AFSCN are characterized by heterogeneous batches of products (i.e. product
quality differs within the batch and between batches) delivered by a diversity of pro-
