遗传算法设计适应度函数 [英] designing fitness function in genetic algorithm

问题描述

我需要求解联立线性方程组(5个方程组，其中7个未知数，即待定问题)，其中变量在很宽的范围内变化 [0-1,00,000].有人可以建议我应该使用什么健身功能吗?

I need to solve simultaneous linear equations (5 equations with 7 unknowns i.e an under-determined problem) where the variables vary over a wide range of [0 - 1,00,000]. Can someone suggest what fitness function I should use?

推荐答案

我想您是指由5个线性方程组和7个变量组成的系统.

I guess you are referring to a system of 5 linear equations with 7 variables.

本文似乎可以显示您的所需信息.基本上，您需要定义一个成本函数，并使用GA将其最小化.在pdf中搜索健身功能"，以确切地了解如何执行此操作.想法是找到某种程度的变量来衡量您的变量对系统的解决方案(或您的情况下的解决方案)的近似程度.

This paper seems to show what you're looking for. You basically need to define a cost function and use the GA to minimize it. Search the pdf for "fitness function" to see exactly how to do this. The idea is to find some measure of how well your set of variable approximates the solution (or a solution in your case) for the system.

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