Author(s)

Mahmoud Masoud^*, Geoff Kent, Erhan Kozan, Shi Qiang Liu

School of Mathematical Sciences, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Australia.

The sugarcane transport system plays a critical role in the overall performance of Australia’s sugarcane industry. An inefficient sugarcane transport system interrupts the raw sugarcane harvesting process, delays the delivery of sugarcane to the mill, deteriorates the sugar quality, increases the usage of empty bins, and leads to the additional sugarcane production costs. Due to these negative effects, there is an urgent need for an efficient sugarcane transport schedule that should be developed by the rail schedulers. In this study, a multi-objective model using mixed integer programming (MIP) is developed to produce an industry-oriented scheduling optimiser for sugarcane rail transport system. The exact MIP solver (IBM ILOG-CPLEX) is applied to minimise the makespan and the total operating time as multi-objective functions. Moreover, the so-called Siding neighbourhood search (SNS) algorithm is developed and integrated with Sidings Satisfaction Priorities (SSP) and Rail Conflict Elimination (RCE) algorithms to solve the problem in a more efficient way. In implementation, the sugarcane transport system of Kalamia Sugar Mill that is a coastal locality about 1050 km northwest of Brisbane city is investigated as a real case study. Computational experiments indicate that high-quality solutions are obtainable in industry-scale applications.

Train Scheduling, Rail Transportation, Sugarcane, Mixed Integer Programming, Heuristics

Masoud, M. , Kent, G. , Kozan, E. and Liu, S. (2016) A New Multi-Objective Model to Optimise Rail Transport Scheduler. Journal of Transportation Technologies, 6, 86-98. doi: 10.4236/jtts.2016.62008.