System and method for train route optimization including machine learning system

A method for optimizing a schedule for railroad vehicles travelling within a railroad network performed by a machine learning system, through operation of at least one processor, comprising:

• receiving, by a machine learning module in communication with an optimization module, a plurality of schedules for railroad vehicles travelling through a track network transmitted by the optimization module,
• prioritizing, by the machine learning module, the plurality of schedules by applying at least one business rule to the plurality of schedules based on dynamically learned behavior, and
• providing, by the machine learning module, a prioritized list of schedules, and further comprising
• generating, by the optimization module, the plurality of schedules using a genetic algorithm, comprising:
• providing an initial population of initial schedules, each schedule comprising first information of a railroad track network and second information of at least one railroad vehicle travelling in the railroad track network for a time instance,
• selecting at least two schedules of the initial schedules, and
• generating a final population of final schedules utilizing crossover operation between selected initial schedules, wherein the second information of the at least one railroad vehicle travelling in the railroad track network are exchanged between the selected initial schedules.