4.5 Applications
ALADINTM has been successfully applied in several case studies in which new supply
chain scenarios have been evaluated. For example, we compared alternative distribution
Table 1. Specific agents in ALADINTM.
Agents Representation
Production unit Food factory or a grower, who produces products with biological
variation in quality and quantity (including seasonality).
Transportation unit Climate controlled truck or vessel with specific temperature and
modified atmosphere settings and related energy use and CO2
emission per unit.
Storing and distribution
unit
Warehouse or retail outlet with specific climate control characteristics
and related energy use and CO2 emission per unit.
Demand unit Market place with demand for products with specific shelf lives,
colours, etc.
Food product Specific food product (e.g., pepper, cut vegetable) with its specific
quality change model, related to the settings of environmental
conditions in time.
Demand controller Explicit modelling of information flow and decision-making activity
that activate the goods flow.
6622 J.G.A.J. van der Vorst et al.
Downloaded by systems (e.g., warehousing, cross docking and different transport modes at different
environmental conditions) for the export of fresh products such as peppers and tomatoes.
Furthermore, new ordering policies for fresh products have been evaluated, in which
a balance is sought between stock-outs and product waste (shrinkage) in retail outlets.
ALADINTM visualises and quantifies the consequences of design choices for the remaining
shelf life of the product and the level of environmental load. In order to illustrate the
advantages of integral decision making and the capabilities of ALADINTM in somewhat
more detail, we discuss one of the case studies in the next section.
5.