Planning Problems in Intermodal Freight Transport ...

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4.1 Drayage Operator A tactical decision of drayage operators is the assignment of freight locations to intermodal terminal service areas. Taylor et al. [34] compare two alternative heuristic methods that seek to reduce total empty and circuitous (out of route) miles incurred during intermodal drayage movements. The first heuristic uses the minimization of circuitous miles as criterion to assign freight to an intermodal terminal. The second heuristic minimizes the sum of total circuity, empty miles associated with the geographical separation of pickups and deliveries and empty miles due to operational fluctuations in inbound and outbound freight demand within a small service area. Both heuristics are tested in a large experimental design. Conclusions are formulated on the appropriateness of each heuristic in particular situations. Spasovic and Morlok [35] use their strategic planning model for the highway portion of rail-truck intermodal transport, described in section 3.1, to develop pricing guidelines for drayage service. The model generates marginal costs of moving loads in the drayage operation. The marginal costs are used to evaluate the efficiency of drayage rates charged by truckers in the current operation as well as rates used in a proposed operation with centralized planning of tractor and trailer movements. The need for railroad management to become aware of the characteristics of drayage operations and the system-wide impacts of drayage movements on the profitability of intermodal transport are indicated. 4.2 Terminal Operator A terminal operator has to decide on the required capacity levels of equipment and labour. Kemper and Fischer [36] model the transfer of containers in an intermodal rail/road
terminal with a single crane. Their objective is to determine quality of service in terms of waiting times and utilisation of resources, especially with regard to the dimensions of the waiting areas for incoming trucks. Stochastic Petri-nets are used as modelling language and results are obtained numerically by computation of the steady state distribution of an associated Markov chain. In Kozan [37] a network model is presented to analyze container progress in a multimodal container terminal. As objective the author minimizes total throughput time, which is the sum of handling and travelling times of containers from the time the ship arrives at the port until the time they are leaving the terminal and in reversed order. The mathematical model can be applied as decision support tool for equipment investments. Long-term data collection should be carried out before implementing the model. Simulation models are also frequently designed to support tactical decisions at an intermodal terminal. Kulick and Sawyer [38] develop a simulation model to support the analysis of labour deployment and other resource capacities at a major intermodal terminal. The model is used to explore areas where container throughput can be improved. Huynh [39] proposes statistical and simulation models to explain the relationship between the availability of yard cranes and truck turn time. Truck turn time is defined as the time it takes a truck to complete a transaction at an intermodal terminal. A second tactical planning problem of terminal operators is the redesign of operational routines and layout structures. Voges et al. [40] analyse operating procedures for an existing terminal. Three questions are studied. How should the dispatcher at the gate and the crane drivers make their decisions on how to continue the process? If a certain crane strategy would result in favourable waiting times for trucks, are the crane drivers able to follow it without computer support? When would it be useful to abandon the strategy and to work intuitively? Average waiting time of trucks serves as performance criterion. A combination of Human
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