How to create simulated annealing objective function?

2015 5 28
2 个回答
更新时间：2015 5 28
3 次查看（30 天）

0 个投票

Hello!
I want to create a objective function for Travelling salesman problem using simulated annealing with global optimization toolbox.
Does anyone have idea how to make these?
Thank you for help

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jan grlica
jan grlica 2015-5-28
Thank you.
Yes i can't look on the second link too.
jan grlica
jan grlica 2015-5-28
编辑：Walter Roberson 2015-5-28
for now my programe is looking like these: one .m file:
clc
close all
clear all
global pot
global y
global x
global bestfval_log
global N
bestfval_log = [];
ime=[1 2 3];
str1 = 'Enka';
str2 = 'Dvojka';
str3 = 'Trojka';
x=[1 2 3];
y=[1 2 3];
N=length(x);
figure ('Name', 'Popotnik');
axes('Color', [0.5 0.5 0.5]);
axis([0 10 0 10]);
hold on;
for i=1:N
plot(x(i), y(i), 'g+');
end
text(x(1),y(1),str1);
text(x(2),y(2),str2);
text(x(3),y(3),str3);
pot=1:N;
x0=[0 0];
[x, fval, exitFlag, output] = simulannealbnd(@kriterijskafunckija, x0);
and my objective function is:
function d = kriterijskafunkcija(pot)
%global pot
global x
global y
global N
%global d
d=0;
for i=1:N-1
d=d+((x(pot(i))-x(pot(i+1)))^2+(y(pot(i))-y(pot(i+1)))^2)^.5;
end
i=N;
d=d+((x(pot(i))-x(pot(1)))^2+(y(pot(i))-y(pot(1)))^2)^.5;
anyone knows how to move forward and make these work

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回答（2 个）

Alan Weiss
Alan Weiss 2015-5-28
编辑：Alan Weiss 2015-5-28

0 个投票

The simulated annealing solver is based on continuous variables by default. Perhaps you could make it work for a custom data type, similar to the genetic algorithm solution. But travelling salesman problems are most easily formulated for integer variables. For solutions, see this MILP example which uses Optimization Toolbox, or this genetic algorithm example using Global Optimization Toolbox and a custom data type.
Alan Weiss
MATLAB mathematical toolbox documentation
Walter Roberson
Walter Roberson 2015-5-28

0 个投票

See my discussion in http://uk.mathworks.com/matlabcentral/answers/220440-simulated-annealing-how-to-solve-this-error as to what the problem is here (the code has exactly the same basic problem here), and as to why it is hard to fix.
The short summary: you can use Simulated Annealing techniques with Traveling Salesperson, but using simulannealbnd() itself for the problem is going to be difficult.

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