Linear Programming Duality

Related lectures (31)

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Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.

Covers Dijkstra's algorithm for shortest path problems and its application in ALL-TO-ONE and ALL-PAIRS algorithms.

Explores the concept of duality in linear programming, discussing the relationship between primal and dual problems.

Explains the process of finding an initial Basic Feasible Solution for linear optimization problems using the Simplex Algorithm.

Covers the concept of matroids, focusing on matroid intersection and the properties of subsets of a ground set.

Explores the formulation of the auxiliary problem in linear optimization and its role in optimal decision-making.

Explores interlacing families of polynomials and 1-sided Ramanujan graphs, focusing on their properties and construction methods.

Discusses the Ford-Fulkerson method and strongly connected components in graph algorithms.

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

Explores nonconvex optimization challenges and strategies, including blind image deconvolution and SDP relaxations.