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Uncertainty is one major cause of complexity in real-life problems. As computational power and quality develop rapidly, it is becoming possible to widely apply intelligent methods to model risk factors and optimize risk levels. The unit complements the units in business analytics, logistics management, supply chain management and warehousing, to provide better understanding of the essence of risk, the process of modelling risk factors, the techniques to assess risks using mixed empirical and subjective tools, and assist adequate and effective decision making. The unit will also offer advanced level operations research methods and techniques. The unit will teach students to model risk, to use econometrics tools for risk assessment, and interpret probabilistic reasoning. Case studies and specific tools in logistics management, logistics strategies and risk management in supply chains shall be incorporated into the unit.

Summary 2019

Unit name Risk Modelling and Optimisation
Unit code JNB536
Credit points 12.5
Faculty/School College of Sciences and Engineering
Australian Maritime College
Discipline Maritime and Logistics Management

Prof Nataliya Nikolova

Teaching staff


Level Postgraduate
Available as student elective? Yes
Breadth Unit? No


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Teaching Pattern

1 x 2-hr lecture and 1 x 1-hr tutorial weekly.


Quiz 1 – 40 questions, 20 marks; Quiz 2 – 40 questions, 20 marks; Solving tasks – 4 tasks for 20 marks; Exam – 40 marks.

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