identify routing of flows in the hinterland of the maritime port of Rotterdam, the
Netherlands, based on customer preferences for different types of services, by
different modes. Case 3 concerns two applications of a very similar nature, one at
national and one at international level. Both involved a relatively light form of truck
pricing and involved responses for changes in vehicle types and routes driven. Case
4 also involved network choices (related to routes of transport including ports), but
was linked to a model of trade relations between regions and sectors over the world.
In the next sections, we introduce each case and discuss the results of the
applications.
4 Carbon Credit Points for City Logistics
The decarbonization solution for urban areas developed by Anand (2015) involves
the case of a city trying to influence the external effects of freight distribution within
its borders. It sets out a policy around a cap-and-trade policy for carbon emissions.
Carbon permits are issued to all carriers entering the city; each trip into the city
requires the use of one carbon credit point. As the number of points is limited
(capped by the maximum volume of carbon emissions that the city wants to allow),
the city government provides an alternative mode of shipping. An Urban Consolidation Centre (UCC), at the border of the inner city area, can be used to deposit
freight destined for the city. From here, electric vehicles of a carrier concessioned by
the city will take the freight to its destination. No petrol or diesel vehicles are allowed
to enter the city, without accompanying carbon credits. As soon as all credits have
been spent, remaining trips must be made via the UCC. Companies are allowed to
trade carbon credit points. The price for trading in this scheme is set by the local
government; the revenues are collected by government and recycled as a subsidy for
the UCC. Credit points are perishable so that carriers cannot accumulate them
(Fig. 2.3).
The situation was modelled using an agent-based formulation, where agents in a
city (government, shopkeepers, carriers, UCC) made decisions. The decisions were
aimed at achieving agent-specific objectives, were cyclical (i.e. reviewed with a
fixed frequency) and, eventually, interdependent. The objective of government was
to reduce the emission levels to a certain target level. Shopkeepers would aim to
minimize their costs (demand being assumed fixed), just like carriers, while the UCC
aimed to achieve a net financial result.
Decisions considered included the following (Fig. 2.4):
• Government: number and price of carbon credits, subsidy to UCC; monthly
decision
• Shopkeepers: order size, carrier to use – daily decision
• Carriers: routing; daily
• UCC: price of transport with EV; monthly
2 The Influence of Logistics Decisions on Transport Decarbonization: Lessons from. . .
23
Netherlands, based on customer preferences for different types of services, by
different modes. Case 3 concerns two applications of a very similar nature, one at
national and one at international level. Both involved a relatively light form of truck
pricing and involved responses for changes in vehicle types and routes driven. Case
4 also involved network choices (related to routes of transport including ports), but
was linked to a model of trade relations between regions and sectors over the world.
In the next sections, we introduce each case and discuss the results of the
applications.
4 Carbon Credit Points for City Logistics
The decarbonization solution for urban areas developed by Anand (2015) involves
the case of a city trying to influence the external effects of freight distribution within
its borders. It sets out a policy around a cap-and-trade policy for carbon emissions.
Carbon permits are issued to all carriers entering the city; each trip into the city
requires the use of one carbon credit point. As the number of points is limited
(capped by the maximum volume of carbon emissions that the city wants to allow),
the city government provides an alternative mode of shipping. An Urban Consolidation Centre (UCC), at the border of the inner city area, can be used to deposit
freight destined for the city. From here, electric vehicles of a carrier concessioned by
the city will take the freight to its destination. No petrol or diesel vehicles are allowed
to enter the city, without accompanying carbon credits. As soon as all credits have
been spent, remaining trips must be made via the UCC. Companies are allowed to
trade carbon credit points. The price for trading in this scheme is set by the local
government; the revenues are collected by government and recycled as a subsidy for
the UCC. Credit points are perishable so that carriers cannot accumulate them
(Fig. 2.3).
The situation was modelled using an agent-based formulation, where agents in a
city (government, shopkeepers, carriers, UCC) made decisions. The decisions were
aimed at achieving agent-specific objectives, were cyclical (i.e. reviewed with a
fixed frequency) and, eventually, interdependent. The objective of government was
to reduce the emission levels to a certain target level. Shopkeepers would aim to
minimize their costs (demand being assumed fixed), just like carriers, while the UCC
aimed to achieve a net financial result.
Decisions considered included the following (Fig. 2.4):
• Government: number and price of carbon credits, subsidy to UCC; monthly
decision
• Shopkeepers: order size, carrier to use – daily decision
• Carriers: routing; daily
• UCC: price of transport with EV; monthly
2 The Influence of Logistics Decisions on Transport Decarbonization: Lessons from. . .
23