How to add a less than constraint condition to solve the transcendental equation
2 次查看(过去 30 天)
显示 更早的评论
I have tried to solve the transcendental equation by Genetic algorithm. The fitness function used for the equations is given below:
function y = myFitnes(x)
y = ((cos(x(1)) + cos(x(2)) + cos(x(3)) + cos(x(4))-0.9*(pi/2)))^2...
+(cos(3*x(1)) + cos(3*x(2)) + cos(3*x(3)) + cos(3*x(4)))^2...
+(cos(5*x(1)) + cos(5*x(2)) + cos(5*x(3)) + cos(5*x(4)))^2 ...
+ (cos(7*x(1)) + cos(7*x(2)) + cos(7*x(3)) + cos(7*x(4)))^2;
end
The main code written to solve the above equation using Genetic algorithm is given below:
objFcn =@myFitnes;
nvars = 4;
LB = [0 0 0 0];
UB = [pi/2 pi/2 pi/2 pi/2];
[x, fval] = ga(objFcn,nvars,[],[],[],[],LB,UB);
How to add the constraint condition 0<x(1)<x(2)<x(3)<x(4)<pi/2; to solve the above equations.
2 个评论
Matt J
2018-1-7
Please indent your code so that it is fonted more readably (as I have done for you now)
采纳的回答
Matt J
2018-1-7
编辑:Matt J
2018-1-7
A=[1,-1,0,0;
0, 1,-1;0;
0, 0, 1,-1];
b=[0;0;0];
objFcn =@myFitnes;
nvars = 4;
LB = [0 0 0 0];
UB = [pi/2 pi/2 pi/2 pi/2];
[x, fval] = ga(objFcn,nvars,A,b,[],[],LB,UB);
4 个评论
Walter Roberson
2018-9-15
[1, -1, 0, 0]*[x1; x2; x3; x4] is x1-x2. Requiring that to be less than b(1)=0 is the condition x1-x2<=0. Add x2 to both sides to get x1<=x2
The A b matrix also encodes x2<=x3 the same way. Transitivity says you can then write x1 <= x2 <= x3 <= x4. The 0 at the beginning is expressed by lb 0. The const at the other end is ub const.
更多回答(1 个)
Walter Roberson
2018-1-7
objFcn =@myFitnes;
nvars = 4;
A = [1 -1 0 0;
0 1 -1 0;
0 0 1 -1]
b = [0;
0;
0];
LB = [0 0 0 0] + realmin; %disallow 0 exactly
UB = [pi/2 pi/2 pi/2 pi/2] * (1-eps); %disallow pi/2 exactly
[x, fval] = ga(objFcn, nvars, A, b, [], [], LB, UB);
This implements 0 < x(1) <= x(2) <= x(3) <= x(4) < pi/2 which is not exactly what you had asked for. Coding strict inequalities would require adding the nonlinear constraint function, which is possible in this case (since you do not have any integer constraints), but is not as efficient.
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Genetic Algorithm 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!