AbstractsComputer Science

Research Doctorate - Doctor of Philosophy (PhD) The Hunter Valley Coal Chain (HVCC) is the largest coal export operation in the world. It concerns the transport of coal from mines located in the Hunter Valley to the Port of Newcastle in New South Wales, Australia. Approximately 1700 coal vessels are loaded at the Port of Newcastle and more than 150 million tonnes of coal is exported each year. The HVCC is a complex system involving 14 producers operating 35 coal mines, 27 coal load points, 2 rail track owners, 4 above rail operators, 3 coal loading terminals with a total of 8 berths, and 9 vessel operators. The coal export supply chain is managed by the Hunter Valley Coal Chain Coordinator (HVCCC). One of the most important and far-reaching decision problems faced by HVCCC is the planning of the long-term capacity. The demand for coal continues to grow and thus the export through the Port of Newcastle is expected to increase in the future. Therefore, the infrastructure needs to be upgraded and the capacities in the system expanded. As upgrading infrastructure and expanding the capacity is extremely expensive, a careful and thorough system analysis is crucial to ensure that investments are made in the right place and at the right time. HVCCC uses an elaborate and detailed simulation model of the HVCC to analyse and assess the throughput of the system, to detect and identify any bottlenecks in the system, and to investigate and explore the benefits of infrastructure upgrades and expansions. As the simulation model is very detailed, it takes a considerable amount of time to run, and as a consequence, a few scenarios can be analysed. We develop an integer programming based decision support tool that quickly assesses the throughput of a coal export supply chain for a given level of demand. The tool can be used to rapidly evaluate a number of infrastructures for several future demand scenarios in order to identify a few that should to be investigated more thoroughly using the detailed simulation model. To make the natural integer programming model computationally tractable, we exploit problem structure to reduce the number of variables, and we employ aggregation as well as disaggregation to strengthen the linear programming relaxation. We use the tool in a computational study in which we analyse system performance for different levels of demand to identify the potential bottlenecks. Afterwards, we discover a symmetry in the integer programming model which contributes to a computational issue. By aggregating certain variables, we suggest an aggregated (implicit) integer programming model that can break the symmetry. Applying the Hall’s marriage theorem and the model structure, we provide the required constraints which make the solution of the aggregated model feasible for the original model. As the number of required constraints is considerably large, and most of them are redundant at the optimal solution, a separation algorithm is designed to find those constraints that are necessary and add them in the search tree. A…