An integrated approach to optimise sugarcane rail operations

• An innovative mathematical model is presented to optimise a cane transport system.
• An integrated depth-first-search algorithm with constraint programming is presented.
• A hybrid metaheuristic technique is developed for finding more accurate solutions with less CPU time.

In Australia, the railway system plays a vital role in transporting the sugarcane crop from farms to mills. The sugarcane transport system is complex as it routines a daily schedule, which consists of a set of train runs to satisfy the requirements of the mills and harvesters. A constrain programming approach is used to formulate this complicated system. Metaheuristic techniques and constraint programming are hybridised as an efficient solution approach. Thus, a better sugarcane transport scheduling system is achieved to maximise the throughput of sugarcane transport. A numerical investigation is presented and demonstrates that high-quality solutions are obtainable for industry-scale applications in a reasonable time.