We developed optimization models for many personnel or vehicle scheduling problems for airline, bus and rail transportation. Each model includes thousands of constraints and millions of millions of variables. We constructed new mathematic methods solving these large problems by working only on a subset of variables and constraints at the time. The dynamic adjustment of the subsets permits to catch the pertinent information and achieve the optimal solution. These systems are commercialized around the world by AD OPT and Giro, two spin-off from the university who hire more than 400 scientists.