How does make function of this equation?
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Can anyone help me,how to implement this equation in MATLAB?
This is basically the fitness function of genetic algorithm.
5 Kommentare
darova
am 22 Dez. 2019
Where is the data?
Misbah Habib
am 22 Dez. 2019
darova
am 22 Dez. 2019
ja nie ponimaju
dpb
am 22 Dez. 2019
Attach expression we can read w/o downloading a file, please...
Misbah Habib
am 23 Dez. 2019
Antworten (3)
Misbah Habib
am 23 Dez. 2019
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1 Kommentar
Walter Roberson
am 23 Dez. 2019
What is the variable of summation? Is the i in gi(j) the same as the i in li-1 ?
The variables potentially used in the summation are i and j, but both of those appear to be used in the bounds of summation.
Walter Roberson
am 23 Dez. 2019
1 / (N * sum(C(sub2ind(size(C), gi(1:end-1), gi(2:end)))))
... under various assumptions about what the equation is intended to mean.
5 Kommentare
Misbah Habib
am 23 Dez. 2019
Walter Roberson
am 23 Dez. 2019
In that case it would generally be more robust to use the negative of the reciprocal, and without the N factor.
Walter Roberson
am 23 Dez. 2019
That is, for optimization you would use
- sum(C(sub2ind(size(C), gi(1:end-1), gi(2:end))))
Again, this depends upon what some of the terms mean. I have interpreted
as indicating that gi is a vector of node numbers, and that
is the "cost" associated with traveling from the node designated by
to the node
and that Cis a matrix not a function. This would, for example, be used in a Travelling Salesman Problem, except that in a Traveling Salesman problem you would be wanting to minimize the sum, not maximize it (maximal sum leads to minimal
)
as indicating that gi is a vector of node numbers, and that
is the "cost" associated with traveling from the node designated by
and that Cis a matrix not a function. This would, for example, be used in a Travelling Salesman Problem, except that in a Traveling Salesman problem you would be wanting to minimize the sum, not maximize it (maximal sum leads to minimal
Misbah Habib
am 24 Dez. 2019
Walter Roberson
am 24 Dez. 2019
When you are doing the optimization, what would the input be?
If the input is a list of nodes forming a path, and you are trying to find an optimal path, then be aware that your current expression will find the path with highest C entries, which is presumably the same thing as the path with the highest cost. The higher the cost of the path, the lower the value of 1/N * 1/cost .
If your C represents distance or represents energy use to transmit from one node to another, then minimizing your
would involving maximizing your cost, which would in turn involve shooting messages as far away as possible and then back closer as the least efficient path would lead to highest sum() and that leads to lowest reciprocal-of-sum.
Misbah Habib
am 24 Dez. 2019
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3 Kommentare
Walter Roberson
am 25 Dez. 2019
numvar = min(size(C,1), size(C,2));
obj = @(gi) -sum(C(sub2ind(size(C), gi(1:end-1), gi(2:end))));
A = []; b = [];
Aeq = []; beq = [];
lb = 1 * ones(1, numvar);
ub = numvar * ones(1, numvar);
nonlcon = @(gi) numvar - length(unique(gi)); %positive if there are duplicates
intcon = 1 : numvar;
[best_gi, cost] = ga(obj, numvar, A, b, Aeq, beq, lb, ub, nonlcon, intcon);
Warning: this is a very inefficient way of expressing that the values must be a permutation of integers !!!
Misbah Habib
am 25 Dez. 2019
Walter Roberson
am 25 Dez. 2019
You would do a lot more efficient with ga() if you did not use intcon and instead used a custom creation and custom mutation and custom crossover functions that "just happened" to impose permutations.
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