OPTIMIZATION BY COMPUTER USING THE GENETIC ALGORITHM

By J. Lopez

This book provides functions for advanced optimization that minimize or maximize objectives while satisfying constraints. Using Matlab includes solvers for linear programming (LP), mixed-integer linear programming (MILP), quadratic programming(QP), nonlinear programming (NLP), constrained linear least squares, nonlinear least squares, and nonlinear equations. Global Optimization Toolbox provides functions that search for global solutions to problems that contain multiple maxima or minima. Toolbox solvers include surrogate, pattern search, genetic algorithm, particle swarm, simulated annealing, multi start, and global search. The genetic algorithm is a method for solving both constrained and unconstrained optimization problems that is based on natural selection, the process that drives biological evolution. The genetic algorithm repeatedly modifies a population of individual solutions. You can apply the genetic algorithm to solve a variety of optimization problems that are not well suited for standard optimization algorithms, including problems in which the objective function is discontinuous, nondifferentiable, stochastic, or highly nonlinear. The genetic algorithm can address problems of mixed integer programming, where some components are restricted to be integer-valued.

• Format: Paperback
• Language: English
• ISBN: B08DBYPVW2
• ISBN13: 9798668412587
• Release Date: July 2020
• Publisher: Independently published
• Length: 233 Pages
• Weight: 0.77 lbs.
• Dimensions: 9.0" x 0.6" x 6.0"