Abstract
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.
Highlights
With around $2.0 billion in export earnings, Australia is the world’s third largest exporter of raw sugar
As most of publications in train scheduling are theoretic, one main contribution of this paper is to develop a real-time optimiser to produce an automatic scheduler for a sugarcane rail transport system, which is adapted as an extended parallel-machine job shop scheduling systems with blocking constraints [15]-[18]
Regarding the development of efficient solution techniques, the second main contribution of this paper is to propose a set of heuristic algorithms in efficiently solving this complicated sugarcane train scheduling problem
Summary
Mahmoud Masoud*, Geoff Kent, Erhan Kozan, Shi Qiang Liu School of Mathematical Sciences, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Australia. Received 31 December 2015; accepted 22 February 2016; published 25 February 2016
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