GA optimization toolbox sover

Hello I am a student of IPE and i am working with VRPWSDP. I want to optimize the travelling distnce in MATLAB by using GA optimization toolbox.But I am unable to write fitness function,linear equality constrants,inequality constraints etc. How will I do it.

7 commentaires

Walter Roberson
Walter Roberson le 21 Déc 2016
I recognize VRP as Vehicle Routing Problem, and the W is "with" but I do not recognize the "SDP" part?
Nilufa Yeasmin
Nilufa Yeasmin le 21 Déc 2016
Modifié(e) : Nilufa Yeasmin le 21 Déc 2016
SDP means simultaneously deliver and Pickup
Nilufa Yeasmin
Nilufa Yeasmin le 22 Déc 2016
Modifié(e) : Nilufa Yeasmin le 22 Déc 2016
Thanks Walter Roberson for your kind response. Now i am working with thirty customer points where no of vehicle,vehicle capacity,customer demand are collected.Actually i want to know how to write fitness function,linear equality,linear inequality constrants in matlab in case of three dimensional by using GA toolbox for minimizing travelling distance.I need help urgently
Walter Roberson
Walter Roberson le 22 Déc 2016
We are not equipped for urgent assistance of any nature.
It is just before 3 AM where I am, and I am going to sleep soon. You have also asked a question that would require a fair bit of research from the regular volunteers, as none of us are familiar with advanced vehicle routing problems. It would be a lot better if you were to ask specific questions. For example start with the matter of what is being optimized. Given any particular configuration, how do you measure how good the configuration is?
For that matter, before that you need to figure out what your variables are. What are the inputs that you you need to vary??
Nilufa Yeasmin
Nilufa Yeasmin le 23 Déc 2016
Thanks Walter Roberson for your advice. I have attach the file for my problem. How can I breakdown this equation in matlab.

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Walter Roberson
Walter Roberson le 23 Déc 2016

0 votes

function cost = objective(x, d)
cost = sum(d(:) .* x(:));
end
To be used with
ga( @(x) objective(x, d), 20*20*5 )

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