Decision Making and Optimisation (BUSA90538)

Graduate courseworkPoints: 12.5On Campus (Parkville)

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Overview

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March
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There is an assortment of mathematical methods to obtain efficient solutions to a large variety of complex business problems. This component helps student formulate a business problem as a mathematical model and then use computational techniques to estimate and solve the model. Topics covered may include decision making under uncertainty, optimal location allocation of resources in business processes, decision trees, linear programming, integer linear programming, and Monte Carlo simulations.

Intended learning outcomes

On completion of this subject, students should be able to:

  • Appreciate the importance and application of mathematical models for solving several problems in business.
  • Understand the most relevant methods and the trade-off between methods required to solve these models including: decision trees, linear programming, integer linear programming, local search and meta-heuristics.
  • Perform optimization techniques to solve business problems.

Last updated: 4 March 2025