The course has two basic parts, organized by model type, stochastic and deterministic. Within each part, we will cover a set of models and solution methodologies. However, the structure of the course will be problem-centric to the largest extent possible. That is, we present the models and solution methodologies in the context of a set of transportation problems. This is not a math course. We will examine the role of these models in an overall methodology of Transportation System Analysis.
The transportation problems we will examine will be taken primarily from air and rail transportation problems. The following table lists the models we will study in the course.
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Probability spaces, random variables |
Networks |
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Distributions, stochastic processes |
Linear programs |
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Queues |
Duality |
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Statistics |
Integer programs |
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Estimation |
Decomposition |
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Hypothesis testing, goodness of fit |
Relaxation |
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Regression, time series |
Heuristics |
Any reading on these topics will be useful to you in preparing yourself for the course. In addition, general reading on transportation problems in trade journals and general press will be beneficial.