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ZEIT4700 – S1, 2014

ZEIT4700 – S1, 2014. Mathematical Modeling and Optimization. School of Engineering and Information Technology. Mathematical Modeling. Definition / Purpose Significance in Optimization Design of Experiments. Optimization - basics. What is Optimization ?

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ZEIT4700 – S1, 2014

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  1. ZEIT4700 – S1, 2014 Mathematical Modeling and Optimization School of Engineering and Information Technology

  2. Mathematical Modeling Definition / Purpose Significance in Optimization Design of Experiments

  3. Optimization - basics What is Optimization ? Why/when is it needed (or not) ? How to define an optimization problem ?

  4. Optimization – types / classification Single-objective / multi-objective Unimodal / multi-modal Single / multi - variable Discrete / continuous / mixed variables Constrained / unconstrained Deterministic / Robust Single / multi-disciplinary

  5. Optimization - methods Classical • Gradient based • Simplex Heuristic / metaheuristics • Evolutionary Algorithms • Simulated Annealing • Ant Colony Optimization • Particle Swarm Optimization . .

  6. Approximations • Surrogate Models / Meta-models • Meta-modelling techniques

  7. Robust optimization Formulation Uncertainty Quantification Search algorithms

  8. Assessment Project 1 (Individual) Project 2 (Individual) Project 3 (Group) Viva

  9. Resources Course material and suggested reading can be accessed at http://seit.unsw.adfa.edu.au/research/sites/mdo/Hemant/design-2.htm

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