2 files changed, 122 insertions, 0 deletions
diff --git a/code/fminunc/SStemperature.sce b/code/fminunc/SStemperature.sce
new file mode 100644
index 0000000..cdbd08d
--- /dev/null
+++ b/code/fminunc/SStemperature.sce
@@ -0,0 +1,53 @@
+//Reference: S.S. Rao,Engineering Optimization Theory and Practice, 3rd enlarged edition, New age international publishers,2011,chapter 6
+// The steady state temperature (t1 and t2) at two points (mid point and the free end) of the one dimensional fin correspond to the minimum of the function. 
+//   f(t1,t2) = 0.6382*t(1)^2 + 0.3191*t(2)^2 - 0.2809*t(1)*t(2) - 67.906*t(1) - 14.29*t(2)
+//=====================================================================
+// 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: Remya Kommadath
+// Organization: FOSSEE, IIT Bombay
+// Email: toolbox@scilab.in
+//=====================================================================
+
+clc; 
+// Objective function
+function f  = ObjectiveFunction(t)
+    f = 0.6382*t(1)^2 + 0.3191*t(2)^2 - 0.2809*t(1)*t(2) - 67.906*t(1) - 14.29*t(2);
+endfunction
+// Initial guess
+x0 = [100 200];
+disp(x0, "Initial guess given to the solver is ")
+input("Press enter to proceed: ")
+[xopt,fopt,exitflag,output,gradient,hessian] = fminunc(ObjectiveFunction,x0)
+// Result representation
+clc
+select exitflag
+case 0 
+    disp("Optimal Solution Found")
+    disp(xopt', "The steady state temperature at the points are")
+    disp(fopt, "The optimum objective function value is")
+case 1
+    disp("Maximum Number of Iterations Exceeded. Output may not be optimal.")
+    disp(xopt', "The temperature at the points are")
+    disp(fopt, "The objective function value is")
+case 2
+    disp("Maximum CPU Time exceeded. Output may not be optimal.")
+    disp(xopt', "The temperature at the points are")
+    disp(fopt, "The objective function value is")
+case 3
+    disp("Stop at Tiny Step.")
+    disp(xopt', "The temperature at the points are")
+    disp(fopt, "The objective function value is")
+case 4
+    disp("Solved To Acceptable Level.")
+    disp(xopt', "The temperature at the points are")
+    disp(fopt, "The objective function value is")
+case 5 
+    disp("Converged to a point of local infeasibility.")
+end
+
+disp(output)
diff --git a/code/fminunc/ThreeHump-backCamel.sci b/code/fminunc/ThreeHump-backCamel.sci
new file mode 100644
index 0000000..f1f2b38
--- /dev/null
+++ b/code/fminunc/ThreeHump-backCamel.sci
@@ -0,0 +1,69 @@
+// Reference: Urmila Diwekar, "Introduction to Aplied Optimization", 2nd Ed, Springer Science + Business Media,2008, Chapter 3
+
+// Three hump-back camel function : An unconstrained problem
+// F(X) = 2*X(1)^2 - 1.05*X(1)^4 + (1/6)*X(1)^6 + X(1)*X(2) + X(2)^2
+// Dimension of the problem:  2
+// The global optima for the function: F*(X) = 0 and X* = [0 0];
+//=====================================================================
+// 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: Remya Kommadath
+// Organization: FOSSEE, IIT Bombay
+// Email: toolbox@scilab.in
+//=====================================================================
+
+clc; 
+// Objective function 
+function f = ObjectiveFunction(X)
+    f = 2*X(1)^2 - 1.05*X(1)^4 + (1/6)*X(1)^6 + X(1)*X(2) + X(2)^2;
+endfunction
+// Gradient of the function
+function gf = GradientFunction(X)
+    gf = [4*X(1) - 4.2*X(1)^3 + X(1)^5 + X(2), X(1) + 2*X(2)];
+endfunction
+// Hessian matrix of the function
+function hf = HessianFunction(X)
+    hf = [4 - 12.6*X(1)^2 + 5*X(1)^4, 1; 1 2]
+endfunction
+
+// Initial guess
+x0 = [0,-1];
+disp(x0, "The initial guess given to the solver is")
+input("Press enter to proceed: ")
+// User specified parameter values
+options=list("gradobj", GradientFunction,"hessian",HessianFunction);
+// Calling the solver
+[xopt,fopt,exitflag,output,gradient,hessian] = fminunc(ObjectiveFunction,x0,options)
+
+// Result representation
+clc
+select exitflag
+case 0 
+    disp("Optimal Solution Found")
+    disp(xopt', "The optimum solution obtained is")
+    disp(fopt, "The optimum objective function value is")
+case 1
+    disp("Maximum Number of Iterations Exceeded. Output may not be optimal.")
+    disp(xopt', "The solution obtained is")
+    disp(fopt, "The objective function value is")
+case 2
+    disp("Maximum CPU Time exceeded. Output may not be optimal.")
+    disp(xopt', "The solution obtained is")
+    disp(fopt, "The objective function value is")
+case 3
+    disp("Stop at Tiny Step.")
+    disp(xopt', "The solution obtained is")
+    disp(fopt, "The objective function value is")
+case 4
+    disp("Solved To Acceptable Level.")
+    disp(xopt', "The solution obtained is")
+    disp(fopt, "The objective function value is")
+case 5 
+    disp("Converged to a point of local infeasibility.")
+end
+
+disp(output)