After this course, the student is able to:
- Create and program mathematical models that model the behavior of transport systems;
- Explain and apply mathematical optimization techniques related to common transport problems (e.g., traffic assignment, transport network design, public transport maintenance, traffic light optimization);
- Apply numerical solution methods in Matlab using optimization solvers (e.g., Gurobi) or self-programmed solution methods
Despite the continuous increase in transport demand over the past decades, it is not always possible to build new infrastructure to increase the transport supply. This has triggered the need to use mathematical optimization to utilize the existing infrastructure as efficiently as possible. This course provides insight in some of the fundamental properties of transport policies and traffic management, where individual choice behavior affects network performance.|
Basic concepts of graph theory, routing problems, characteristics of graphs, optimization problems with and without boundary conditions, linear programming, Lagrangian and Karush-Kuhn-Tucker conditions, bi-level and multi-variate optimization methods, convex optimization, heuristic equilibration techniques and evolutionary algorithms will be applied to common transport problems to improve efficiency.
The main topics covered in the course are:
- Application of graph theory, combinatorial optimization and nonlinear optimization to transport problems;
- Route set generation and choice in transport networks;
- Constrained and Unconstrained optimization;
- Development of mathematical optimization models for common transport problems, e.g. Network Design Problem and Transportation planning, including maintenance and operations.
This course will be assessed by means of assignments.