This lecture introduces the fundamental concepts of optimization and operations research, focusing on modeling complex decision-making problems in engineering, business, analytics, and mathematical sciences. It covers key topics such as mathematical optimization, simulation, queuing theory, and data analysis. The lecture explores real-world examples like cargo loading, train timetabling, and network design for battery electric buses. The course structure includes self-learning, interactive sessions, and exercise sessions, organized around six topics over a semester. Students will delve into linear optimization, simplex algorithm, networks, transshipment, discrete optimization, and nonlinear optimization, with a final exam to assess their understanding.
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