6 files changed, 0 insertions, 308 deletions
diff --git a/demos/exam.sce b/demos/exam.sce
deleted file mode 100644
index e054eff..0000000
--- a/demos/exam.sce
+++ /dev/null
@@ -1,5 +0,0 @@
-function y = f(x) 
-  y = 3*x(1)^2 + 2*x(1)*x(2) + x(2)^2 - 4*x(1) + 5*x(2) ;
-endfunction
-
-[xval, fval, status, gradient, hessian] = intfminbnd(f,[1], [1 2],[2 6])
diff --git a/demos/intfminbnd.dem.sce b/demos/intfminbnd.dem.sce
deleted file mode 100644
index adbc9fa..0000000
--- a/demos/intfminbnd.dem.sce
+++ /dev/null
@@ -1,55 +0,0 @@
-mode(1)
-//
-// Demo of intfminbnd.sci
-//
-
-//Find x in R^6 such that it minimizes:
-//f(x)= sin(x1) + sin(x2) + sin(x3) + sin(x4) + sin(x5) + sin(x6)
-//-2 <= x1,x2,x3,x4,x5,x6 <= 2
-//Objective function to be minimised
-function y=f(x)
-y=0
-for i =1:6
-y=y+sin(x(i));
-end
-endfunction
-//Variable bounds
-x1 = [-2, -2, -2, -2, -2, -2];
-x2 = [2, 2, 2, 2, 2, 2];
-intcon = [2 3 4]
-//Options
-options=list("MaxIter",[1500],"CpuTime", [100])
-[x,fval] =intfminbnd(f ,intcon, x1, x2, options)
-// Press ENTER to continue
-halt()   // Press return to continue
- 
-//Find x in R such that it minimizes:
-//f(x)= 1/x^2
-//0 <= x <= 1000
-//Objective function to be minimised
-function y=f(x)
-y=1/x^2;
-endfunction
-//Variable bounds
-x1 = [0];
-x2 = [1000];
-intcon = [1];
-[x,fval,exitflag,output,lambda] =intfminbnd(f,intcon , x1, x2)
-// Press ENTER to continue
-halt()   // Press return to continue
- 
-//The below problem is an unbounded problem:
-//Find x in R^2 such that it minimizes:
-//f(x)= -[(x1-1)^2 + (x2-1)^2]
-//-inf <= x1,x2 <= inf
-//Objective function to be minimised
-function y=f(x)
-y=-((x(1)-1)^2+(x(2)-1)^2);
-endfunction
-//Variable bounds
-x1 = [-%inf , -%inf];
-x2 = [ %inf , %inf];
-//Options
-options=list("MaxIter",[1500],"CpuTime", [100])
-[x,fval,exitflag,output,lambda] =intfminbnd(f,intcon, x1, x2, options)
-//========= E N D === O F === D E M O =========//
diff --git a/demos/intfmincon.dem.sce b/demos/intfmincon.dem.sce
deleted file mode 100644
index ef43b4b..0000000
--- a/demos/intfmincon.dem.sce
+++ /dev/null
@@ -1,136 +0,0 @@
-mode(1)
-//
-// Demo of intfmincon.sci
-//
-
-//Find x in R^2 such that it minimizes:
-//f(x)= -x1 -x2/3
-//x0=[0,0]
-//constraint-1 (c1): x1 + x2 <= 2
-//constraint-2 (c2): x1 + x2/4 <= 1
-//constraint-3 (c3): x1 - x2 <= 2
-//constraint-4 (c4): -x1/4 - x2 <= 1
-//constraint-5 (c5): -x1 - x2 <= -1
-//constraint-6 (c6): -x1 + x2 <= 2
-//constraint-7 (c7): x1 + x2 = 2
-//Objective function to be minimised
-function [y,dy]=f(x)
-y=-x(1)-x(2)/3;
-dy= [-1,-1/3];
-endfunction
-//Starting point, linear constraints and variable bounds
-x0=[0 , 0];
-intcon = [1]
-A=[1,1 ; 1,1/4 ; 1,-1 ; -1/4,-1 ; -1,-1 ; -1,1];
-b=[2;1;2;1;-1;2];
-Aeq=[1,1];
-beq=[2];
-lb=[];
-ub=[];
-nlc=[];
-//Options
-options=list("GradObj", "on");
-//Calling Ipopt
-[x,fval,exitflag,grad,hessian] =intfmincon(f, x0,intcon,A,b,Aeq,beq,lb,ub,nlc,options)
-// Press ENTER to continue
-halt()   // Press return to continue
- 
-//Find x in R^3 such that it minimizes:
-//f(x)= x1*x2 + x2*x3
-//x0=[0.1 , 0.1 , 0.1]
-//constraint-1 (c1): x1^2 - x2^2 + x3^2 <= 2
-//constraint-2 (c2): x1^2 + x2^2 + x3^2 <= 10
-//Objective function to be minimised
-function [y,dy]=f(x)
-y=x(1)*x(2)+x(2)*x(3);
-dy= [x(2),x(1)+x(3),x(2)];
-endfunction
-//Starting point, linear constraints and variable bounds
-x0=[0.1 , 0.1 , 0.1];
-intcon = [2]
-A=[];
-b=[];
-Aeq=[];
-beq=[];
-lb=[];
-ub=[];
-//Nonlinear constraints
-function [c,ceq,cg,cgeq]=nlc(x)
-c = [x(1)^2 - x(2)^2 + x(3)^2 - 2 , x(1)^2 + x(2)^2 + x(3)^2 - 10];
-ceq = [];
-cg=[2*x(1) , -2*x(2) , 2*x(3) ; 2*x(1) , 2*x(2) , 2*x(3)];
-cgeq=[];
-endfunction
-//Options
-options=list("MaxIter", [1500], "CpuTime", [500], "GradObj", "on","GradCon", "on");
-//Calling Ipopt
-[x,fval,exitflag,output] =intfmincon(f, x0,intcon,A,b,Aeq,beq,lb,ub,nlc,options)
-// Press ENTER to continue
-halt()   // Press return to continue
- 
-//The below problem is an unbounded problem:
-//Find x in R^3 such that it minimizes:
-//f(x)= -(x1^2 + x2^2 + x3^2)
-//x0=[0.1 , 0.1 , 0.1]
-//  x1 <= 0
-//  x2 <= 0
-//  x3 <= 0
-//Objective function to be minimised
-function y=f(x)
-y=-(x(1)^2+x(2)^2+x(3)^2);
-endfunction
-//Starting point, linear constraints and variable bounds
-x0=[0.1 , 0.1 , 0.1];
-intcon = [3]
-A=[];
-b=[];
-Aeq=[];
-beq=[];
-lb=[];
-ub=[0,0,0];
-//Options
-options=list("MaxIter", [1500], "CpuTime", [500]);
-//Calling Ipopt
-[x,fval,exitflag,grad,hessian] =intfmincon(f, x0,intcon,A,b,Aeq,beq,lb,ub,[],options)
-// Press ENTER to continue
-halt()   // Press return to continue
- 
-//The below problem is an infeasible problem:
-//Find x in R^3 such that in minimizes:
-//f(x)=x1*x2 + x2*x3
-//x0=[1,1,1]
-//constraint-1 (c1): x1^2 <= 1
-//constraint-2 (c2): x1^2 + x2^2 <= 1
-//constraint-3 (c3): x3^2 <= 1
-//constraint-4 (c4): x1^3 = 0.5
-//constraint-5 (c5): x2^2 + x3^2 = 0.75
-// 0 <= x1 <=0.6
-// 0.2 <= x2 <= inf
-// -inf <= x3 <= 1
-//Objective function to be minimised
-function [y,dy]=f(x)
-y=x(1)*x(2)+x(2)*x(3);
-dy= [x(2),x(1)+x(3),x(2)];
-endfunction
-//Starting point, linear constraints and variable bounds
-x0=[1,1,1];
-intcon = [2]
-A=[];
-b=[];
-Aeq=[];
-beq=[];
-lb=[0 0.2,-%inf];
-ub=[0.6 %inf,1];
-//Nonlinear constraints
-function [c,ceq,cg,cgeq]=nlc(x)
-c=[x(1)^2-1,x(1)^2+x(2)^2-1,x(3)^2-1];
-ceq=[x(1)^3-0.5,x(2)^2+x(3)^2-0.75];
-cg = [2*x(1),0,0;2*x(1),2*x(2),0;0,0,2*x(3)];
-cgeq = [3*x(1)^2,0,0;0,2*x(2),2*x(3)];
-endfunction
-//Options
-options=list("MaxIter", [1500], "CpuTime", [500], "GradObj", "on","GradCon", "on");
-//Calling Ipopt
-[x,fval,exitflag,grad,hessian] =intfmincon(f, x0,intcon,A,b,Aeq,beq,lb,ub,nlc,options)
-// Press ENTER to continue
-//========= E N D === O F === D E M O =========//
diff --git a/demos/intfminimax.dem.sce b/demos/intfminimax.dem.sce
deleted file mode 100644
index db74b92..0000000
--- a/demos/intfminimax.dem.sce
+++ /dev/null
@@ -1,57 +0,0 @@
-mode(1)
-//
-// Demo of intfminimax.sci
-//
-
-// A basic case :
-// we provide only the objective function and the nonlinear constraint
-// function
-function f = myfun(x)
-f(1)= 2*x(1)^2 + x(2)^2 - 48*x(1) - 40*x(2) + 304;     //Objectives
-f(2)= -x(1)^2 - 3*x(2)^2;
-f(3)= x(1) + 3*x(2) -18;
-f(4)= -x(1) - x(2);
-f(5)= x(1) + x(2) - 8;
-endfunction
-// The initial guess
-x0 = [0.1,0.1];
-// The expected solution : only 4 digits are guaranteed
-xopt = [4 4]
-fopt = [0 -64 -2 -8 0]
-intcon = [1]
-maxfopt = 0
-// Run fminimax
-[x,fval,maxfval,exitflag] = intfminimax(myfun, x0,intcon)
-// Press ENTER to continue
-halt()   // Press return to continue
- 
-// A case where we provide the gradient of the objective
-// functions and the Jacobian matrix of the constraints.
-// The objective function and its gradient
-function [f,G] = myfun(x)
-f(1)= 2*x(1)^2 + x(2)^2 - 48*x(1) - 40*x(2) + 304;
-f(2)= -x(1)^2 - 3*x(2)^2;
-f(3)= x(1) + 3*x(2) -18;
-f(4)= -x(1) - x(2);
-f(5)= x(1) + x(2) - 8;
-G = [ 4*x(1) - 48, -2*x(1), 1, -1, 1;
-2*x(2) - 40, -6*x(2), 3, -1, 1; ]'
-endfunction
-// The nonlinear constraints
-function [c,ceq,DC,DCeq] = confun(x)
-// Inequality constraints
-c = [1.5 + x(1)*x(2) - x(1) - x(2), -x(1)*x(2) - 10]
-// No nonlinear equality constraints
-ceq=[]
-DC= [x(2)-1, -x(2);
-x(1)-1, -x(1)]'
-DCeq = []'
-endfunction
-// Test with both gradient of objective and gradient of constraints
-minimaxOptions = list("GradObj","on","GradCon","on");
-// The initial guess
-x0 = [0,10];
-intcon = [2]
-// Run intfminimax
-[x,fval,maxfval,exitflag] = intfminimax(myfun,x0,intcon,[],[],[],[],[],[], confun, minimaxOptions)
-//========= E N D === O F === D E M O =========//
diff --git a/demos/intfminunc.dem.sce b/demos/intfminunc.dem.sce
deleted file mode 100644
index 97cbb2d..0000000
--- a/demos/intfminunc.dem.sce
+++ /dev/null
@@ -1,49 +0,0 @@
-mode(1)
-//
-// Demo of intfminunc.sci
-//
-
-//Find x in R^2 such that it minimizes the Rosenbrock function
-//f = 100*(x2 - x1^2)^2 + (1-x1)^2
-//Objective function to be minimised
-function y= f(x)
-y= 100*(x(2) - x(1)^2)^2 + (1-x(1))^2;
-endfunction
-//Starting point
-x0=[-1,2];
-intcon = [2]
-//Options
-options=list("MaxIter", [1500], "CpuTime", [500]);
-//Calling
-[xopt,fopt,exitflag,gradient,hessian]=intfminunc(f,x0,intcon,options)
-// Press ENTER to continue
-halt()   // Press return to continue
- 
-//Find x in R^2 such that the below function is minimum
-//f = x1^2 + x2^2
-//Objective function to be minimised
-function y= f(x)
-y= x(1)^2 + x(2)^2;
-endfunction
-//Starting point
-x0=[2,1];
-intcon = [1];
-[xopt,fopt]=intfminunc(f,x0,intcon)
-// Press ENTER to continue
-halt()   // Press return to continue
- 
-//The below problem is an unbounded problem:
-//Find x in R^2 such that the below function is minimum
-//f = - x1^2 - x2^2
-//Objective function to be minimised
-function [y,g,h] = f(x)
-y = -x(1)^2 - x(2)^2;
-g = [-2*x(1),-2*x(2)];
-h = [-2,0;0,-2];
-endfunction
-//Starting point
-x0=[2,1];
-intcon = [1]
-options = list("gradobj","ON","hessian","on");
-[xopt,fopt,exitflag,gradient,hessian]=intfminunc(f,x0,intcon,options)
-//========= E N D === O F === D E M O =========//
diff --git a/demos/intqpipopt.dem.sce b/demos/intqpipopt.dem.sce
deleted file mode 100644
index 7c63476..0000000
--- a/demos/intqpipopt.dem.sce
+++ /dev/null
@@ -1,6 +0,0 @@
-mode(1)
-//
-// Demo of intqpipopt.sci
-//
-
-//========= E N D === O F === D E M O =========//