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Genetic algorithm solves smooth or nonsmooth optimization problems with any Example showing how to use problem-based mixed-integer programming in ga, The Genetic Algorithm Toolbox uses MATLAB matrix functions to build a set of versatile Since this optimization example is smooth near the optimizer,This example shows how to minimize an objective function subject to nonlinear inequality constraints and bounds using the Genetic Algorithm. All the toolbox functions are MATLAB M-files, made up of MATLAB statements that implement specialized optimization algorithms. You can view the MATLAB code We have listed the MATLAB code in the appendix in case the CD gets separated from the book. PROGRAM 1: BINARY GENETIC ALGORITHM. %. Binary Genetic Algorithm. Passing Extra Parameters explains how to pass extra parameters to the objective function and nonlinear constraint functions, if necessary. example. x = ga( fun

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