Discrete Optimization: Traveling Salesman Problem

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Page 3 of 4

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

Covers the theory and applications of optimization with constraints, including key concepts and numerical methods.

Explores relations between events, disjunctive constraints, and modeling with binary variables in optimization problems.

Explores Quadratic Penalty Methods for optimization with enforced constraints using penalty functions.

Covers fundamental concepts of optimization and operations research, exploring real-world examples and key topics over a semester.

Introduces linear algebra, calculus, and optimization basics in Euclidean spaces, emphasizing the power of optimization as a modeling tool.

Introduces the two-phase simplex algorithm and explores duality in linear programming.

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

Explains linear constraints and variable elimination in optimization problems, illustrating the process step by step.

Covers single inequality or equality constraints and necessary optimality conditions in optimization problems.