Microeconomic Consumer Theory

Related lectures (31)

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Explains the process of finding an initial Basic Feasible Solution for linear optimization problems using the Simplex Algorithm.

Covers fundamental concepts of optimization and operations research, exploring real-world examples and key topics over a semester.

Covers optimization techniques in machine learning, focusing on convexity and its implications for efficient problem-solving.

Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.

Explores self-dual cones in convex optimization and their applications in various optimization problems.

Explores optimization problems and greedy algorithms to find the best solutions efficiently.

Introduces state-triggered constraints for non-prehensile manipulation and showcases improved performance through feedback control.

Covers energy system modelling, optimization, scenarios, predictions, complexities, and controversies in energy models.

Covers dynamic programming with a focus on Fibonacci numbers and efficient calculation algorithms.

Covers the basics of the Simplex method and its application in solving optimization problems.