Exact Methods for Integer Optimization

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Approximation Algorithms

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

Optimization Methods: Theory Discussion

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

Exact methods: Branch and Bound MOOC: Optimization: principles and algorithms - Network and discrete optimization

Explores the Branch and Bound algorithm in discrete optimization, efficiently finding optimal solutions by calculating lower bounds on subsets.

Optimization: Classical Problems

Covers classical optimization problems, brute force algorithms, and integer linear optimization.

Optimisation in Energy Systems

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

Discrete Optimization: Relaxation MOOC: Optimization: principles and algorithms - Network and discrete optimization

Explores solving discrete optimization problems by relaxing integrality constraints.

Optimization and Simulation

Explores greedy heuristics in optimization, integrality constraints, and comparison of optimization methods.

Hedging for LPs

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

Linear Programming: Weighted Bipartite Matching

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

Nonlinear Optimization Methods

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

Discrete optimization: Knapsack MOOC: Optimization: principles and algorithms - Network and discrete optimization

Explores modeling classic optimization problems as mixed integer linear problems, focusing on the knapsack problem and its applications.

Discrete Optimization: Definitions MOOC: Optimization: principles and algorithms - Network and discrete optimization

Covers definitions and concepts in discrete optimization, including binary linear problems and combinatorial optimization.

Optimisation Problem: Solving by FM

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

Cutset Formulation: MST Problem Log in to Mediaspace to watch this video

Explores the cutset formulation for the MST Problem and Gomory Cutting Planes method.

Branch & Bound Algorithm: LP Based Approach Log in to Mediaspace to watch this video

Explores the LP-based Branch & Bound algorithm for finding optimal solutions.

Branch & Bound: Optimization Log in to Mediaspace to watch this video

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

Optimal Decision Making: Integer Programming Log in to Mediaspace to watch this video

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

Integer Optimization Log in to Mediaspace to watch this video

Covers optimization problems, minimal packing, and bounds in Integer Optimization.

Optimization Principles Log in to Mediaspace to watch this video

Covers optimization principles, including linear optimization, networks, and concrete research examples in transportation.

Optimal Decision Making: Applications of Discrete Optimization Log in to Mediaspace to watch this video

Explores optimal decision making through discrete optimization, emphasizing binary variables and practical applications.

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