Optimization Principles

Related lectures (31)

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Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.

Explains network flows, LP formulations, simplex method, duality, and practical applications.

Explores the simplex algorithm and how optimal solutions can be found on vertices of constraint polyhedra.

Covers optimization problems in path finding and portfolio allocation.

Covers the process of solving Linear Programs (LPs) using the simplex method.

Explains the SIMPLEX method for solving linear programs and optimizing the solution through basis variable manipulation.

Explores the concept of duality in linear programming and its practical implications in optimization.

Explores duality in linear programming, strong duality, complementary slackness, and the economic interpretation of dual variables as prices.

Covers the formulation of optimization programs for minimizing piecewise linear cost functions.

Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.