Genetic Algorithm - Relation between Population and Fitness Function

3 次查看（过去 30 天）

Sam 2014-1-26

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/113743-genetic-algorithm-relation-between-population-and-fitness-function

评论： Sam 2014-2-21

When using a Custom Population Function and specifically Custom Binary Population. How does the population relate to the Fitness Function?

I have both coded out but and have somewhat knowledge but lack the critical understanding of how they work together. Should my fitness function have a input variable which takes in the population and computes the fitness of the individuals?

I have not found and detailed reading material on this relation. Are there any such reading materials available on these relations or could anyone explain them please.

Thanks.

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Alan Weiss 2014-1-27

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/113743-genetic-algorithm-relation-between-population-and-fitness-function#answer_122311

编辑：Alan Weiss 2014-1-27

在 MATLAB Online 中打开

As described in the documentation, the creation function creates a population, and the fitness function evaluates how good each member of the population is. There is a specific syntax for the creation function, and there is a syntax for the fitness function. There is more information about fitness functions here.

For the creation function, the syntax is

function population = creationfcn(nvars,fitnessfcn,options)

GA passes the arguments nvars, fitnessfcn, and options to your creation function. What you do with those arguments is up to you. You will certainly need the nvars argument so that your population has the right number of elements, but you can use the other two arguments or ignore them as you see fit.

There is an example of a custom data type here.

I hope this helps.

Alan Weiss MATLAB mathematical toolbox documentation

12 个评论
显示 10更早的评论隐藏 10更早的评论

Alan Weiss 2014-1-28

I am sorry, I do not understand you. I do not know what a chromosome function is, or is supposed to be.

It is somewhat unfortunate that MATLAB solvers force you to put your problem into the syntax they expect, instead of one that seems natural to you. But if you want to use our solvers, you have to somehow use our syntax.

So, if you want to use GA, I suggest that you try to reformulate your problem our way. Write a fitness function that either takes a single individual and computes its fitness, or takes an entire population and returns a vector of the fitness of all the individuals. Separate your constraints into bounds, linear constraints, and nonlinear constraints, and put those into the expected places in the GA syntax.

I hope you understand what I am suggesting. Yes, it can seem unnatural to go through all these extra steps, and possibly to take your "chromosome function" apart and distribute its functionality across a bunch of different things (ftness function, constraints, maybe population creation too). But I believe that is what you need to do.

Of course, it is possible that I misunderstand you entirely. If so, I apologize.

Good luck,

Alan Weiss

MATLAB mathematical toolbox documentation

Sam 2014-2-19

在 MATLAB Online 中打开

HI Alan! I really have to thank you very much for entertaining my queries all this while... they have been extremely helpful and has steepened my learning curve!

I have successfully completed my problem formulation and have managed to Optimize using GA. I do have 1 more query though to which i would hope to get some advice from you on..

I am currently running GA in which my Population is a Double Vector as i had issues with my creation function. But, i am not getting an ideal result since the values are purely stochastic... i can control them to a certain extent with the use of Upper & Lower Bounds but it is not sufficient.

I realize i will certainly obtain a better fitness if i use a custom population since i can supply further constraints within the custom data type to generate an ideal pseudo random integer.

I currently have my Creation Function written out but not sure how i am to pass it through GA yet. Could you kindly explain please. Specifically on the Syntax you had supplied in your answer.

Currently I have

function result = cust_pop()

The variable 'result' will hold a value of 1x100 where 100 is my nVars also. My current implementation is not following your guide as above. Please advise on what i need to change to make it work.

Thanks!

Alan Weiss 2014-2-21

在 MATLAB Online 中打开

Sam, I suggest that you try going through the introductory documentation on how to set up an optimization in Optimization Problem Setup. The link I gave to Linear Inequality Constraints should show you how to include these constraints. Here is an extensive example in the context of linear programming.

Basically, to make a linear inequality constraint

A*x <= b

you simply pass the A matrix and b vector in the solver. For ga,

x = ga(objective,numvariables,A,b,...)

Then ga will automatically ensure that the constraints are satisfied. Please do not use any custom creation, mutation, or crossover functions, or ga might not keep the linear inequalities.

Good luck,

Alan Weiss

MATLAB mathematical toolbox documentation

Sam 2014-2-21

ohh sorry let me rephrase.. i am aware of this and have done this more than a few times now... i meant to ask how should the constraints be sent in since i need to write it in A & b format...

but after going through the documentation links for awhile now it is clearer i had confused myself by accident...

Thanks much!

请先登录，再进行评论。