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OVERVIEW
Optimization Solutions Optimization is often used to find values of variables that yield a minimum or maximum function value. It usually considers the problem of minimization because maximization of f(x) can be achieved by simply minimizing -f(x) There exists a variety of optimization methods that can be applied to real-world engineering problems. These type of algorithms are iterative in nature that require starting values for the variables. There are various techniques for the solution of optimization problems. At KMP we developed algorithms applicable for functions with a single variable (one-dimensional space) and optimizations for functions with multiple variables. For single variable function we show the Bisection Method and the Simplex Method for multi-variable functions. Please select from the menu  →         OPTIMIZATION ALGORITHMS  (press to select)

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EIGENVALUE SOLUTIONS...
Eigen Inverse Iteration
Rayleigh-Quotient Method

INTERPOLATION APPLICATIONS...
Cubic Spline Method
Newton Divided Difference

 Applied Mathematical Algorithms Complex Functions A complex number z = x + iy, where... Complex Functions Non-Linear Systems Non-linear system methods... Non Linear Systems Differentiation Construction of differentiation... Differentiation Integration Consider the function where... Integration