Explores the Branch and Bound algorithm in discrete optimization, efficiently finding optimal solutions by calculating lower bounds on subsets.
Covers the main idea behind the Simplex algorithm and explains the Tableau method for solving linear programming problems.
Covers methods for solving nonlinear optimization problems, including direct search, Newton-Raphson, and branch and bound.
Covers the basics of optimization, including historical perspectives, mathematical formulations, and practical applications in decision-making problems.
