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This lecture introduces various methods for solving nonlinear optimization problems, starting with direct and indirect search approaches, followed by heuristic methods. The instructor explains how to transform inequality constraints into equality constraints using slack variables and discusses the Newton-Raphson method for solving nonlinear equations. The lecture also covers the Lagrange equivalence and the branch and bound method for handling integer variables in optimization problems.