Branch and Bound: Heuristic Maximization

Related lectures (32)

Page 3 of 4

Covers sensitivity analysis in linear programming, focusing on optimal solutions and their sensitivities to changes.

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

Explores solving discrete optimization problems by relaxing integrality constraints.

Covers solving integer linear programs graphically, algorithmically, and through optimization methods.

Introduces the basics of integer programming, including binary integer programs and constraint strategies.

Explores the concept of duality in linear programming and its practical implications in optimization.

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.

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

Explores integer programs, nonconvex optimization, constraints, and geometric aspects of linear programming for optimal solutions.

Covers B+ Trees, a key data structure for efficient indexing in databases.