Optimal Decision Making: Integer Programming

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Optimal Decision Making: Sensitivity Analysis

Covers sensitivity analysis in linear programming, focusing on optimal solutions and their sensitivities to changes.

Branch & Bound: Optimization

Covers the Branch & Bound algorithm for efficient exploration of feasible solutions and discusses LP relaxation, portfolio optimization, Nonlinear Programming, and various optimization problems.

Hedging for LPs

Covers the concept of hedging for Linear Programs and the simplex method, focusing on minimizing costs and finding optimal solutions.

Optimisation Problem: Solving by FM

Covers the modelling and optimization of energy systems, focusing on solving optimization problems with constraints and variables.

Simplex Algorithm: Exercises & Interpretation

Covers exercises on the Simplex Algorithm, optimizing solutions subject to linear constraints.

Integer Programs: Optimization and Constraints

Explores integer programs, nonconvex optimization, constraints, and geometric aspects of linear programming for optimal solutions.

Linear Programming Techniques in Reinforcement Learning

Covers the linear programming approach to reinforcement learning, focusing on its applications and advantages in solving Markov decision processes.

Convex Polyhedra and Linear Programs

Explores convex polyhedra, linear programs, and their optimization importance.

Energy System Modeling: Optimization and Performance Indicators

Explores energy system modeling using optimization techniques and performance indicators.

Linear Programming: Convex Hull

Covers MAE regression, convex hull, reformulation advantages, and practical problems with decision variables and constraints.