In path finding algorithms from a source to a destination, shortest path algorithms are widely known and currently used in common advance driver assistance systems. However, in some specific applications such as dangerous goods transport, the minimization of the typical objective related to the travel cost (e.g. distance, time etc…) has to find a trade-off with another objective, which is the minimization of the risk and the exposure of the population to such risk. This multi-objective problem, which may be driven by a risk averse behaviour, has also important relationships with some behaviours which can be found in simple living beings surviving to risk in nature, sometimes also known as “playing against nature” problems. Some basic theory and practical examples will be shown.
The most widely used modelling approaches for freeway traffic networks will be described together with the existing schemes for regulating the dynamic behaviour of traffic in the considered transportation systems. Attention will be focused on applied methods and real case studies as well as on the most advanced and innovative research approaches.
Abderrahmane Habbal (INRIA)
When solving multi-optimization problems (multi -criteria, -point or -disciplinary ones), the first challenge is to set the relevant definition of what is to be computed. We shall discuss pros and cons of three approaches, scalarization, Pareto Front capture and Game formulations. The last one is quite new, and opens promising perspectives of handling complex concurrent design in engineering. The lecture will introduce all necessary theoretical material, and present some industrial applications.