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Lecture
Simplex Algorithm
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Related lectures (32)
Linear Programming: Weighted Bipartite Matching
Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.
Hedging for LPs
Covers the concept of hedging for Linear Programs and the simplex method, focusing on minimizing costs and finding optimal solutions.
Simplex Algorithm: Tableau
MOOC: Optimization: principles and algorithms - Linear optimization
Covers the main idea behind the Simplex algorithm and explains the Tableau method for solving linear programming problems.
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.
Simplex Algorithm: Graphical Method
MOOC: Optimization: principles and algorithms - Linear optimization
Illustrates the simplex algorithm through a graphical method to find optimal solutions.
Discrete Optimization: Relaxation
MOOC: Optimization: principles and algorithms - Network and discrete optimization
Explores solving discrete optimization problems by relaxing integrality constraints.
Simplex Algorithm: Solution on a Vertex
MOOC: Optimization: principles and algorithms - Linear optimization
Explores the simplex algorithm and how optimal solutions can be found on vertices of constraint polyhedra.
Simplex Algorithm: Exercises & Interpretation
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Covers exercises on the Simplex Algorithm, optimizing solutions subject to linear constraints.
Optimal Decision Making: Sensitivity Analysis
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Covers sensitivity analysis in linear programming, focusing on optimal solutions and their sensitivities to changes.
Linear Programming Basics
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Introduces linear programming basics, including optimization problems, cost functions, simplex algorithm, geometry of linear programs, extreme points, and degeneracy.
Simplex Algorithm: Basics
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Introduces the Simplex algorithm for solving flow problems and handling negative cost cycles.
Optimization Problems: Path Finding and Portfolio Allocation
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Covers optimization problems in path finding and portfolio allocation.
Cutset Formulation: MST Problem
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Explores the cutset formulation for the MST Problem and Gomory Cutting Planes method.
Local Sensitivity Analysis: Feasibility and Optimality
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Explores local sensitivity analysis in linear programming, examining how changes impact optimality and feasibility.
Linear Optimization: Auxiliary Problem
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Explores the formulation of the auxiliary problem in linear optimization and its role in optimal decision-making.
Optimization Principles
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Covers optimization principles, including linear optimization, networks, and concrete research examples in transportation.
Linear Programming: Two-phase Simplex Algorithm
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Covers the application of the two-phase Simplex algorithm to solve linear programming problems.
Optimal Decision Making: The Simplex Method
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Introduces the Simplex Method for optimal decision making in linear programming, covering basic and advanced concepts.
Convex Polyhedra and Linear Programs
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Explores convex polyhedra, linear programs, and their optimization importance.
Linear Programming: Solving LPs
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Covers the process of solving Linear Programs (LPs) using the simplex method.
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