Search - genetic algorithm minimization

Search - genetic algorithm minimization - List

[AI-NN-PR] webinar_files DL : 0: This a demonstration of how to find a minimum of a non-smooth objective function using the Genetic Algorithm (GA) function in the Genetic Algorithm and Direct Search Toolbox. Traditional derivative-based optimization methods, like those found in the Optimization Toolbox, are fast and accurate for many types of optimization problems. These methods are designed to solve smooth , i.e., continuous and differentiable, minimization problems, as they use derivatives to determine the direction of descent. While using derivatives makes these methods fast and accurate, they often are not effective when problems lack smoothness, e.g., problems with discontinuous, non-differentiable, or stochastic objective functions. When faced with solving such non-smooth problems, methods like the genetic algorithm or the more recently developed pattern search methods, both found in the Genetic Algorithm and Direct Search Toolbox, are effective alternatives. -This is a demonstration of how to find a minimum of a non-smooth objective function using the Genetic Algorithm (GA) function in the Genetic Algorithm and Direct Search Toolbox. Traditional derivative-based optimization methods, like those found in the Optimization Toolbox, are fast and accurate for many types of optimization problems. These methods are designed to solve smooth , i.e., continuous and differentiable, minimization problems, as they use derivatives to determine the direction of descent. While using derivatives makes these methods fast and accurate, they often are not effective when problems lack smoothness, e.g., problems with discontinuous, non-differentiable, or stochastic objective functions. When faced with solving such non-smooth problems, methods like the genetic algorithm or the more recently developed pattern search methods, both found in the Genetic Algorithm and Direct Search Toolbox, are effective alternatives.
Date : 2025-07-15 Size : 18kb User : gao
[Software Engineering] ll DL : 0: 一个遗传算法的函数优化，求函数的最小值，matlab编写的程序-A genetic algorithm for function optimization, seeking the minimization, matlab program written
Date : 2025-07-15 Size : 1kb User : zuodongsheng
[AI-NN-PR] GA_method DL : 0: 直接使用实数编写的遗传算法，简单易行，不需要适应函数为正，可以计算含有约束的最小化问题-Prepared directly using the real genetic algorithm, is simple, do not meet the function is positive, can be calculated with constrained minimization problem
Date : 2025-07-15 Size : 2kb User : sunff
[matlab] Genetic-Algorithms-using-Matlab DL : 0: This document contend matlab source codes about genetic algorithm.The codes try to minimization of any kind of function.-This document contend matlab source codes about genetic algorithm.The codes try to minimization of any kind of function.
Date : 2025-07-15 Size : 606kb User : ibo
[VHDL-FPGA-Verilog] fault DL : 0: fault minimization using genetic algorithm
Date : 2025-07-15 Size : 1.57mb User : thangapandiyan
[matlab] DG-GA DL : 0: Multiple distributed generation units allocation in distribution network for loss reduction based on a combination of analytical and genetic algorithm methods
Date : 2025-07-15 Size : 374kb User : jattboy