On Time with Rail-Traffic Optimization Technology

Problems with Existing Optimization Approaches Traditional optimization software employs a linear decisionmaking process whereby a single solution is reached. Traditional optimization techniques generally seek a single solution, such as maximizing profit or reducing cost. Each change in the environment (e.g., train delays or equipment fault) triggers the optimization system to start again from scratch to search for a new solution. This approach is both time-consuming and unrealistic for effective use in planning real-time train movement. In contrast, standard planning of train movement requires several objectives to be addressed simultaneously, e.g., minimizing the cost of crews and minimizing lateness.