Optimization Course Competencies

Students gain an understanding of the principles and techniques of optimization, including linear and nonlinear programming, decision analysis, and simulation. A focus of the course is to develop and apply optimization models to solve real-world engineering problems. Students analyze and interpret the results of optimization models, including sensitivity analysis and model robustness. Importantly, they communicate the results of optimization models effectively after developing implementation strategies for optimization models in software environments. There is some development and application of optimization models in the context of multi-objective optimization. Meta-heuristic optimization techniques are covered with the basics of evolutionary algorithms and simulated annealing. An additional course covers the basics of artificial intelligence and machine learning techniques. The optimization methods in this course are foundational for machine learning.

Course Objectives

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