Transport companies often discover that what takes place in day-to-day transportation is not in line with their transport plans. This is largely due to the fact that the software which is employed in creating transport plans, fails to account for the real-world complexity of transportation and logistics. Approximations and abstractions used fall short of the true complexities in the real world. Direct consequences include violation of time windows, unnecessary delays, underutilized transportation capacity, etc.
This project aims to develop algorithms and software that can handle time-dependent, stochastic, planning problems, employing high-volumes of information. We will focus particularly on the complexities that arise in integrating planning problems and stochastic dependencies in Cross Chain Control Centers (4C), because in a 4C: i) the required real-life detail increases, ii) incidents are considerably larger, and iii) more communication is required as the pressure on response time increases.