diff options
Diffstat (limited to 'code/fmincon')
-rw-r--r-- | code/fmincon/Tankprob.sci | 95 | ||||
-rw-r--r-- | code/fmincon/spring.sci | 120 |
2 files changed, 215 insertions, 0 deletions
diff --git a/code/fmincon/Tankprob.sci b/code/fmincon/Tankprob.sci new file mode 100644 index 0000000..500090e --- /dev/null +++ b/code/fmincon/Tankprob.sci @@ -0,0 +1,95 @@ +//Design a circular tank, closed at both ends, with a volume of 200 m3.The cost is proportional to the surface area of material, which is priced +//at $400/m2. The tank is contained within a shed with a sloping roof,thus the height of the tank h is limited by h ≤ 12 − d/2, where d is +//the tank diameter. Formulate the minimum cost problem and solve the design problem. +//Ref:Diwekar, Urmila,Introduction to Applied Optimization, Introduction to Applied Optimization, Editor:Ding-Zhu Du, Springer Optimization and Its Applications Springer Optimization and Its Applications, VOL 22, Chapter 3 + +// Copyright (C) 2018 - IIT Bombay - FOSSEE +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author:Debasis Maharana +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +//====================================================================== + +clc; + +function cost = Tankprob(x) + r = x(1);h = x(2); + cost = (2*%pi*r*h+2*%pi*r^2)*400; +endfunction + +function [ceq,c] = Nonlinearcon(x) + r = x(1);h = x(2); + c = []; + ceq = 200-%pi*r^2*h; +endfunction + +function y=Gradobj(x) + y= [800*%pi*x(2) + 1600*%pi*x(1),800*%pi*x(1)]; +endfunction + +mprintf('\nDesign a circular tank, closed at both ends, with a volume of 200 m3 with minimum cost.\n The tank is contained within a shed with a sloping roof,thus the height of the tank h is limited') +mprintf('\nCost of material is: %f',400); +mprintf('The design variables are radius and height of the tank') + +A = [1 1];b = 12; + +x0 = input('Enter initial guess as vector:'); +if (sum(x0<=0) | (length(x0)~=2)) + x0 = [1 2]; + mprintf('Incorrect initial guess...\n changing initial guess to r = %d and h = %d',x0(1),x0(2)); +end + + +lb = [0 0]; +input('press enter to continue') +options=list("MaxIter",1000,"GradObj", Gradobj); + +[xopt,fopt,exitflag,output1] = fmincon(Tankprob,x0,A,b,[],[],lb,[],Nonlinearcon,options); + +[xopt1,fopt1,exitflag1,output2] = fmincon(Tankprob,x0,A,b,[],[],lb,[],Nonlinearcon); + +clc +select exitflag +case 0 + mprintf('Optimal Solution Found'); + mprintf('\nThe optimal radius and height of the tank are %f m and %f m',xopt(1),xopt(2)); + mprintf('\nThe volume of the tank is %f m^3',%pi*xopt(1)^2*xopt(2)); + mprintf('\nThe total surface area and cost of the tank are %f m^2 and %f $',fopt/400,fopt) + mprintf('\nTime taken to solve the problem with gradient information is %f s and without gradient information is %f s',output1.Cpu_Time,output2.Cpu_Time); +case 1 + mprintf('Maximum Number of Iterations Exceeded. Output may not be optimal'); + input('press enter to view results'); + printf('\nThe optimal radius and height of the tank are %f m and %f m',xopt(1),xopt(2)); + mprintf('\nThe volume of the tank is %f m^3',%pi*xopt(1)^2*xopt(2)); + mprintf('\nThe total surface area and cost of the tank are %f m^2 and %f $',fopt/400,fopt) +case 2 + mprintf('Maximum amount of CPU Time exceeded. Output may not be optimal.'); + input('press enter to view results'); + printf('\nThe optimal radius and height of the tank are %f m and %f m',xopt(1),xopt(2)); + mprintf('\nThe volume of the tank is %f m^3',%pi*xopt(1)^2*xopt(2)); + mprintf('\nThe total surface area and cost of the tank are %f m^2 and %f $',fopt/400,fopt) +case 3 + mprintf('Stop at Tiny Step'); + input('press enter to view results'); + printf('\nThe optimal radius and height of the tank are %f m and %f m',xopt(1),xopt(2)); + mprintf('\nThe volume of the tank is %f m^3',%pi*xopt(1)^2*xopt(2)); + mprintf('\nThe total surface area and cost of the tank are %f m^2 and %f $',fopt/400,fopt) +case 4 + mprintf('Solved To Acceptable Level'); + input('press enter to view results'); + printf('\nThe optimal radius and height of the tank are %f m and %f m',xopt(1),xopt(2)); + mprintf('\nThe volume of the tank is %f m^3',%pi*xopt(1)^2*xopt(2)); + mprintf('\nThe total surface area and cost of the tank are %f m^2 and %f $',fopt/400,fopt) +case 5 + mprintf('Converged to a point of local infeasibility.'); + input('press enter to view results'); + printf('\nThe optimal radius and height of the tank are %f m and %f m',xopt(1),xopt(2)); + mprintf('\nThe volume of the tank is %f m^3',%pi*xopt(1)^2*xopt(2)); + mprintf('\nThe total surface area and cost of the tank are %f m^2 and %f $',fopt/400,fopt) +end + + diff --git a/code/fmincon/spring.sci b/code/fmincon/spring.sci new file mode 100644 index 0000000..0409dce --- /dev/null +++ b/code/fmincon/spring.sci @@ -0,0 +1,120 @@ +//The problem consists of minimizing the weight of a tension/compression spring subject to constraints on +//minimum deflection, shear stress, surge frequency, limits on outside diameter and on design variables. The design +//variables are the mean coil diameter D, the wire diameter d and the number of active coils N. The problem can be +//expressed as follows: +//Min f(x) = ( N + 2)*D*d^2 +//ST +//g1(x) = 1-D^3*N/(71785*d^4) <= 0; +//g2(x) = 1-140.45*d/(D^2*N) <= 0; +//g3(x) = (4*D^2-d*D)/(12566*(d^3*D-d^4)) + 1/(5108*d^2)-1 <= 0; +//g4(x) = (D+d)/1.5 - 1 <=0; +//The following ranges for the variables were used +//0.05 <= d <= 2.0, 0.25<= D <=1.3, 2.0<=N<=15.0 +// +//Ref:Arora, J. S.. Introduction IO optimum design New York McGraw-Hill, 1989 +//====================================================================== +// Copyright (C) 2018 - IIT Bombay - FOSSEE +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +// Author:Debasis Maharana +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in +//====================================================================== +clc; + +function y = spring(x) + y = (x(3)+2)*x(1)^2*x(2); +endfunction + +function [C,Ceq] = Nonlinconstraint(x) + C(1) = 1-x(2)^3*x(3)/(71785*x(1)^4); + C(2) = 1-140.45*x(1)/(x(2)^2*x(3)); + C(3) = (4*x(2)^2-x(1)*x(2))/(12566*(x(1)^3*x(2)-x(1)^4)) + 1/(5108*x(1)^2)-1; + Ceq = [];C = C'; +endfunction + +function f = fGrad(x) + f = [2*x(1)*x(2)*(x(3)+2) x(1)^2*(x(3)+2) x(1)^2*x(2)]; +endfunction + +mprintf('minimizing the weight of a tension/compression spring '); +mprintf('\n\n Design variables include mean coil diameter:D, the wire diameter:d and the number of active coils:N '); +disp('The objective is :( N + 2)*D*d^2'); +mprintf('\nNon-linear constraints are on minimum deflection, shear stress, surge frequency,'); +mprintf('\nlinear constraint is on outside diameter'); + + +A = [1 1 0]; +b = 1.5; +mprintf('Bounds on the variable are as follows'); + +lb = [0.05 0.25 2]; +ub = [2 1.3 15]; +table = [['bounds', 'lb','ub'];[['d';'D';'N'],string(lb'),string(ub')]]; +disp(table); +x0 = lb + rand(1)*(ub-lb); +disp(x0,'Initial Guess is :'); + +input('press enter to continue'); + +mprintf('Scilab is solving your problem'); +options=list("MaxIter", [1500], "CpuTime", [500], "GradObj", fGrad); + +[xopt,fval,exitflag,output] =fmincon(spring, x0,A,b,[],[],lb,ub,Nonlinconstraint,options); + +clc +select exitflag +case 0 + mprintf('Optimal Solution Found'); + mprintf('\n\nThe optimal design parameters are d = %f ,D = %f and N = %f m',xopt(1),xopt(2),xopt(3)); + mprintf('\n\nThe optimal objective is %f ',fval); + mprintf('\n\nIterations completed %d',output.Iterations); + mprintf('\nTotal CPU time %f',output.Cpu_Time); + mprintf('\nTotal Functional Evaluations %d',output.Objective_Evaluation); +case 1 + mprintf('Maximum Number of Iterations Exceeded. Output may not be optimal'); + input('press enter to view results'); + mprintf('\nThe optimal design parameters are d = %f ,D = %f and N = %f m',xopt(1),xopt(2),xopt(3)); + mprintf('\nThe optimal objective is %f ',fval); + mprintf('\nIterations completed %d',output.Iterations); + mprintf('\nTotal CPU time %f',output.Cpu_Time); + mprintf('\nTotal Functional Evaluations %d',output.Objective_Evaluation); +case 2 + mprintf('Maximum amount of CPU Time exceeded. Output may not be optimal.'); + input('press enter to view results'); + mprintf('\nThe optimal design parameters are d = %f ,D = %f and N = %f m',xopt(1),xopt(2),xopt(3)); + mprintf('\nThe optimal objective is %f ',fval); + mprintf('\nIterations completed %d',output.Iterations); + mprintf('\nTotal CPU time %f',output.Cpu_Time); + mprintf('\nTotal Functional Evaluations %d',output.Objective_Evaluation); +case 3 + mprintf('Stop at Tiny Step'); + input('press enter to view results'); + mprintf('\nThe optimal design parameters are d = %f ,D = %f and N = %f m',xopt(1),xopt(2),xopt(3)); + mprintf('\nThe optimal objective is %f ',fval); + mprintf('\nIterations completed %d',output.Iterations); + mprintf('\nTotal CPU time %f',output.Cpu_Time); + mprintf('\nTotal Functional Evaluations %d',output.Objective_Evaluation); +case 4 + mprintf('Solved To Acceptable Level'); + input('press enter to view results'); + mprintf('\nThe optimal design parameters are d = %f ,D = %f and N = %f m',xopt(1),xopt(2),xopt(3)); + mprintf('\nThe optimal objective is %f ',fval); + mprintf('\nIterations completed %d',output.Iterations); + mprintf('\nTotal CPU time %f',output.Cpu_Time); + mprintf('\nTotal Functional Evaluations %d',output.Objective_Evaluation); +case 5 + mprintf('Converged to a point of local infeasibility.'); + input('press enter to view results'); + mprintf('\nThe optimal design parameters are d = %f ,D = %f and N = %f m',xopt(1),xopt(2),xopt(3)); + mprintf('\nThe optimal objective is %f ',fval); + mprintf('\nIterations completed %d',output.Iterations); + mprintf('\nTotal CPU time %f',output.Cpu_Time); + mprintf('\nTotal Functional Evaluations %d',output.Objective_Evaluation); +end + + + |