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Lecture
Branch & Bound Algorithm: LP Based Approach
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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.
Approximation Algorithms
Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Optimization Problems: Path Finding and Portfolio Allocation
Covers optimization problems in path finding and portfolio allocation.
Cutset Formulation: MST Problem
Explores the cutset formulation for the MST Problem and Gomory Cutting Planes method.
Optimal Decision Making: Sensitivity Analysis
Covers sensitivity analysis in linear programming, focusing on optimal solutions and their sensitivities to changes.
Optimization Methods: Theory Discussion
Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.
Linear Programming: Two-phase Simplex Algorithm
Covers the application of the two-phase Simplex algorithm to solve linear programming problems.
Integer Optimization: Theory and Applications
Covers the fundamentals of integer optimization, including integer programming, dynamic programming, and approximation algorithms.
Optimisation in Energy Systems
Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.
Linear Programming: Weighted Bipartite Matching
Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.
