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Diffstat (limited to 'macros/fgoalattain.sci')
| -rw-r--r-- | macros/fgoalattain.sci | 139 |
1 files changed, 38 insertions, 101 deletions
diff --git a/macros/fgoalattain.sci b/macros/fgoalattain.sci index d6bec24..41c0fcc 100644 --- a/macros/fgoalattain.sci +++ b/macros/fgoalattain.sci @@ -1,58 +1,47 @@ -// Scilab ( http://www.scilab.org/ ) - This file is part of Scilab // Copyright (C) 2015 - IIT Bombay - FOSSEE // -// Authors: Prajwala TM,Sheetal Shalini -// Organization: FOSSEE, IIT Bombay -// Email: prajwala.tm@gmail.com,sheetalsh456@gmail.com // 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 +// Authors: Prajwala TM,Sheetal Shalini +// Organization: FOSSEE, IIT Bombay +// Email: toolbox@scilab.in function [x,fval,attainfactor,exitflag,output,lambda] = fgoalattain(varargin) // Solves a multiobjective goal attainment problem // // Calling Sequence - // x = fgoalattain(fun,x0,goal,weight) - // x = fgoalattain(fun,x0,goal,weight,A,b) - // x = fgoalattain(fun,x0,goal,weight,A,b,Aeq,beq) - // x = fgoalattain(fun,x0,goal,weight,A,b,Aeq,beq,lb,ub) - // x = fgoalattain(fun,x0,goal,weight,A,b,Aeq,beq,lb,ub,nonlcon) - // x = fgoalattain(fun,x0,goal,weight,A,b,Aeq,beq,lb,ub,nonlcon,options) - // [x,fval] = fgoalattain(...) - // [x,fval,attainfactor] = fgoalattain(...) - // [x,fval,attainfactor,exitflag] = fgoalattain(...) - // [x,fval,attainfactor,exitflag,output] = fgoalattain(...) - // [x,fval,attainfactor,exitflag,output,lambda] = fgoalattain(...) + // xopt = fgoalattain(fun,x0,goal,weight) + // xopt = fgoalattain(fun,x0,goal,weight,A,b) + // xopt = fgoalattain(fun,x0,goal,weight,A,b,Aeq,beq) + // xopt = fgoalattain(fun,x0,goal,weight,A,b,Aeq,beq,lb,ub) + // xopt = fgoalattain(fun,x0,goal,weight,A,b,Aeq,beq,lb,ub,nonlcon) + // xopt = fgoalattain(fun,x0,goal,weight,A,b,Aeq,beq,lb,ub,nonlcon,options) + // [xopt,fval] = fgoalattain(...) + // [xopt,fval,attainfactor] = fgoalattain(...) + // [xopt,fval,attainfactor,exitflag] = fgoalattain(...) + // [xopt,fval,attainfactor,exitflag,output] = fgoalattain(...) + // [xopt,fval,attainfactor,exitflag,output,lambda] = fgoalattain(...) // // Parameters // fun: a function that accepts a vector x and returns a vector F - // x0: a nx1 or 1xn matrix of double, where n is the number of variables. - // The initial guess for the optimization algorithm - // A: a nil x n matrix of double, where n is the number of variables and - // nil is the number of linear inequalities. - // - // b: a nil x 1 matrix of double, where nil is the number of linear - // inequalities - // Aeq: a nel x n matrix of double, where n is the number of variables - // and nel is the number of linear equalities. - // beq: a nel x 1 matrix of double, where nel is the number of linear - // equalities - // lb: a nx1 or 1xn matrix of double, where n is the number of variables. - // The lower bound for x. If lb==[], then the lower bound is - // automatically set to -inf - // ub: a nx1 or 1xn matrix of double, where n is the number of variables. - // The upper bound for x. If ub==[], then the upper bound is - // automatically set to +inf - // nonlcon: a function, the nonlinear constraints - // options : a list, containing the option for user to specify. See below for details. - // x: a nx1 matrix of double, the computed solution of the optimization problem - // fval: a vector of double, the value of functions at x - // attainfactor: The amount of over- or underachievement of the goals,γ at the solution. - // exitflag: a 1x1 matrix of floating point integers, the exit status - // output: a struct, the details of the optimization process - // lambda: a struct, the Lagrange multipliers at optimum + // x0 : a vector of double, contains initial guess of variables. + // A : a matrix of double, represents the linear coefficients in the inequality constraints A⋅x ≤ b. + // b : a vector of double, represents the linear coefficients in the inequality constraints A⋅x ≤ b. + // Aeq : a matrix of double, represents the linear coefficients in the equality constraints Aeq⋅x = beq. + // beq : a vector of double, represents the linear coefficients in the equality constraints Aeq⋅x = beq. + // lb : a vector of double, contains lower bounds of the variables. + // ub : a vector of double, contains upper bounds of the variables. + // nonlcon: a function, the nonlinear constraints + // options : a list, containing the option for user to specify. See below for details. + // xopt : a vector of double, the computed solution of the optimization problem. + // fopt : a double, the value of the function at x. + // attainfactor: The amount of over- or underachievement of the goals,γ at the solution. + // exitflag : The exit status. See below for details. + // output : The structure consist of statistics about the optimization. See below for details. + // lambda : The structure consist of the Lagrange multipliers at the solution of problem. See below for details. // // Description // fgoalattain solves the goal attainment problem, which is one formulation for minimizing a multiobjective optimization problem. @@ -164,21 +153,12 @@ function [x,fval,attainfactor,exitflag,output,lambda] = fgoalattain(varargin) // f1(5)=x(1)+x(2)-8 // endfunction // x0=[-1,1]; - // // goal=[-5,-3,-2,-1,-4]; // weight=abs(goal) - // gval = - // [- 0.0000011 - // - 63.999998 - // - 2.0000002 - // - 8. - // 3.485D-08] - // z = - // [4. 3.99] - // - // Run fgoalattain - // [x,fval,attainfactor,exitflag,output,lambda]=fgoalattain(gattainObjfun,x0,goal,weight) - // + // //gval =[- 0.0000011 -63.999998 -2.0000002 -8 3.485D-08] + // //z = [4 3.99] + // //Run fgoalattain + // [x,fval,attainfactor,exitflag,output,lambda]=fgoalattain(gattainObjfun,x0,goal,weight) // Authors // Prajwala TM, Sheetal Shalini , 2015 @@ -311,14 +291,14 @@ function [x,fval,attainfactor,exitflag,output,lambda] = fgoalattain(varargin) //To check the User Entry for Options and storing it for i = 1:(size(gattainUserOptions))/2 - select gattainUserOptions(2*i-1) - case "MaxIter" then + select convstr(gattainUserOptions(2*i-1),'l') + case "maxiter" then fgaMaxIter = gattainUserOptions(2*i); //Setting the Maximum Iteration as per user entry - case "CpuTime" then + case "cputime" then fgaCPU = gattainUserOptions(2*i); //Setting the Maximum CPU Time as per user entry - case "GradObj" then + case "gradobj" then if (type(gattainUserOptions(2*i))==10) then if (convstr(gattainUserOptions(2*i))=="off") then flag1 = 0; @@ -331,7 +311,7 @@ function [x,fval,attainfactor,exitflag,output,lambda] = fgoalattain(varargin) gattainFGrad = gattainUserOptions(2*i); end - case "GradCon" then + case "gradcon" then if (type(gattainUserOptions(2*i))==10) then if (convstr(gattainUserOptions(2*i))=="off") then flag2 = 0; @@ -479,49 +459,6 @@ function [x,fval,attainfactor,exitflag,output,lambda] = fgoalattain(varargin) end endfunction - - // disp(gattainStartpoint) - // disp(gattainObjfun(gattainStartpoint)) - // disp(newObjfun(gattainStartpoint)) - // disp(goal) - // disp(weight) - // - // disp(gattainA) - // disp(gattainB) - // disp(gattainAeq) - // disp(gattainBeq) - // disp(gattainLb) - // disp(gattainUb) - // - // [f,g] = gattainNonlinfun(gattainStartpoint) - // disp(f) - // disp(g) - // [f,g] = newNonlinfun(gattainStartpoint) - // disp(f) - // disp(g) - // - // // function foo = CgattainC(z) - // // [foo,tmp1] = newNonlinfun(z) - // // endfunction - // // - // // function foo = CgattainCEQ(z) - // // [tmp1,foo] = newNonlinfun(z) - // // endfunction - // // - // // // function handle defining gattainNonlinfun derivative using numderivative - // // function [dc,dceq] = derrNonlinApp(z) - // // dc = numderivative(CgattainC,z) - // // dceq = numderivative(CgattainCEQ,z) - // // endfunction - // - // // [f,g] = derrNonlinApp(gattainStartpoint) - // // disp(f) - // // disp(g) - // - // [f,g] = newCGrad(gattainStartpoint) - // disp(f) - // disp(g) - //to be passed as options to fmincon if (flag1 == 1 | flag2 == 1) then gattainPassOptions = list("MaxIter", fgaMaxIter, "CpuTime", fgaCPU, "GradCon", newCGrad) |