Two-Stage Stochastic Programs

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Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.

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

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

Covers semi-definite programming and optimization over positive semidefinite cones.

Covers the optimization with constraints, focusing on the Karush-Kuhn-Tucker (KKT) conditions.

Explores energy system modeling using optimization techniques and performance indicators.

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

Explores energy systems modeling, optimization, and cost analysis for efficient operations.

Covers weak and strong duality in optimization problems, focusing on Lagrange multipliers and KKT conditions.