Branch & Bound: Optimization

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Covers methods for solving nonlinear optimization problems, including direct search, Newton-Raphson, and branch and bound.

Optimal Decision Making: Exercises & Solutions

Covers exercises and solutions in translating text problems into linear programming and optimizing decision-making processes.

Optimization Programs: Piecewise Linear Cost Functions

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

Optimisation Problem: Solving by FM

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

Branch and Bound: Optimization Techniques

Covers the Branch and Bound optimization technique with LP Relaxation and Integral Optimal Solutions.

Portfolio Optimization: Models and Strategies

Explores portfolio optimization models and strategies under uncertainty, emphasizing decision criteria like value-at-risk and mean-variance functional.

Optimal Decision Making: Integer Programming

Covers integer programming, convex hulls, Gomory cutting planes, and branch and bound methods.

Linear Programming: Optimization and Constraints

Introduces linear programming, emphasizing optimization with constraints and practical examples.

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.

Optimization in Engineering

Explores optimization methods in engineering, covering decision variables, constraints, and various solving techniques.