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Learning outcomes for the course
On completion of the course, students will be able to:1. critically analyse and formulate practical problems within the class of general operations research problems, and situate them in a structured decision framework
2. design and justify formulations of practical problems, such as linear or integer programming models, while taking into account model assumptions and limitations
3. develop, implement, and evaluate algorithms for solving linear and integer programming problems, and analyse their computational efficiency
4. classify computational problems into complexity classes based on the computational resources that are required to obtain exact solutions, and discuss the implications for applications
5. design, implement, and evaluate heuristic and meta-heuristic approximation methods for addressing computationally intractable problems, and assess their performance relative to exact methods
6. analyse and quantify the complexity of complex dynamical systems, characterise their key properties, and distinguish them from random and chaotic systems.