C ================================================================= C File: penshubert.f C ================================================================= C ================================================================= C Module: Subroutines that define the problem C ================================================================= C Last update of any of the component of this module: C Jun 2, 2006. C Users are encouraged to download periodically updated versions of C this code at the TANGO home page: C www.ime.usp.br/~egbirgin/tango/ C Penalized Shubert function C Problem proposed in: C M. Locatelli, F. Schoen. "Numerical Experience with Random Linkage C Algorithms for Global Optimisation", Technical Report 15-98, C Dip. di Sistemi e Informatica, Universita di Firenze, Italy, 1998. C ****************************************************************** C ****************************************************************** subroutine inip(n,x,l,u,m,lambda,rho,equatn,linear) implicit none C This subroutine must set some problem data. For achieving this C objective YOU MUST MODIFY it according to your problem. See below C where your modifications must be inserted. C C Parameters of the subroutine: C C On Entry: C C This subroutine has no input parameters. C C On Return C C n integer, C number of variables, C C x double precision x(n), C initial point, C C l double precision l(n), C lower bounds on x, C C u double precision u(n), C upper bounds on x, C C m integer, C number of constraints (excluding the bounds), C C lambda double precision lambda(m), C initial estimation of the Lagrange multipliers, C C rho double precision rho(m), C initial penalty parameters. C C equatn logical equatn(m) C for each constraint j, set equatn(j) = .true. if it is an C equality constraint of the form c_j(x) = 0, and set C equatn(j) = .false. if it is an inequality constraint of C the form c_j(x) <= 0, C C linear logical linear(m) C for each constraint j, set linear(j) = .true. if it is a C linear constraint, and set linear(j) = .false. if it is a C nonlinear constraint. C SCALAR ARGUMENTS integer m,n C ARRAY ARGUMENTS logical equatn(*),linear(*) double precision l(*),lambda(*),rho(*),u(*),x(*) C LOCAL SCALARS integer i C ****************************************************************** C FROM HERE ON YOU MUST MODIFY THE SUBROUTINE TO SET YOUR PROBLEM C DATA: C ****************************************************************** C Number of variables n = 2 C Initial point do i = 1,n x(i) = 0.0d0 end do C Lower and upper bounds do i = 1,n l(i) = -10.0d0 u(i) = 10.0d0 end do C Number of constraints (equalities plus inequalities) m = 0 C ****************************************************************** C STOP HERE YOUR MODIFICATIONS OF SUBROUTINE INIP. C ****************************************************************** end C ****************************************************************** C ****************************************************************** subroutine evalf(n,x,f,flag) implicit none C This subroutine must compute the objective function. For achieving C this objective YOU MUST MODIFY it according to your problem. See C below where your modifications must be inserted. C C Parameters of the subroutine: C C On Entry: C C n integer, C number of variables, C C x double precision x(n), C current point, C C On Return C C f double precision, C objective function value at x, C C flag integer, C You must set it to any number different of 0 (zero) if C some error ocurred during the evaluation of the objective C function. (For example, trying to compute the square root C of a negative number, dividing by zero or a very small C number, etc.) If everything was o.k. you must set it C equal to zero. C SCALAR ARGUMENTS integer flag,n double precision f C ARRAY ARGUMENTS double precision x(n) C LOCAL SCALARS integer i,j double precision fsum,dj,beta C Objective function C ****************************************************************** C FROM HERE ON YOU MUST MODIFY THE SUBROUTINE TO SET YOUR OBJECTIVE C FUNCTION: C ****************************************************************** flag = 0 C penalized shubert C SET beta CONSTANT beta = 1.0d0 C SET f f = 1.0d0 do i = 1,n fsum = 0.0d0 do j = 1,5 dj = dble( j ) fsum = fsum + dj * cos( ( dj + 1.0d0 ) * x(i) + dj ) end do f = f * fsum end do f = f + beta * ( ( x(1) + 1.42513d0 ) ** 2.0d0 + + ( x(2) + 0.80032d0 ) ** 2.0d0 ) C ****************************************************************** C STOP HERE YOUR MODIFICATIONS OF SUBROUTINE EVALF. C ****************************************************************** end C ****************************************************************** C ****************************************************************** subroutine evalg(n,x,g,flag) implicit none C This subroutine must compute the gradient vector of the objective C function. For achieving these objective YOU MUST MODIFY it in the C way specified below. However, if you decide to use numerical C derivatives (we dont encourage this option at all!) you dont need C to modify evalg. C C Parameters of the subroutine: C C On Entry: C C n integer, C number of variables, C C x double precision x(n), C current point, C C On Return C C g double precision g(n), C gradient vector of the objective function evaluated at x, C C flag integer, C You must set it to any number different of 0 (zero) if C some error ocurred during the evaluation of any component C of the gradient vector. (For example, trying to compute C the square root of a negative number, dividing by zero or C a very small number, etc.) If everything was o.k. you C must set it equal to zero. C SCALAR ARGUMENTS integer flag,n C ARRAY ARGUMENTS double precision g(n),x(n) C LOCAL SCALARS integer i,j double precision dj,beta C LOCAL ARRAYS double precision fsum(n),dsum(n) C Gradient vector C ****************************************************************** C FROM HERE ON YOU MUST MODIFY THE SUBROUTINE TO SET THE GRADIENT C VECTOR OF YOUR OBJECTIVE FUNCTION: C ****************************************************************** flag = 0 C penalized shubert C SET beta CONSTANT beta = 1.0d0 C SET g do i = 1,n fsum(i) = 0.0d0 dsum(i) = 0.0d0 do j = 1,5 dj = dble( j ) fsum(i) = fsum(i) + dj + * cos( ( dj + 1.0d0 ) * x(i) + dj ) dsum(i) = dsum(i) - dj * sin( ( dj + 1.0d0 ) + * x(i) + dj ) * ( dj + 1.0d0 ) end do end do g(1) = dsum(1) * fsum(2) + 2.0d0 * beta * ( x(1) + 1.42513d0 ) g(2) = dsum(2) * fsum(1) + 2.0d0 * beta * ( x(2) + 0.80032d0 ) C ****************************************************************** C STOP HERE YOUR MODIFICATIONS OF SUBROUTINE EVALG. C ****************************************************************** end C ****************************************************************** C ****************************************************************** subroutine evalh(n,x,hlin,hcol,hval,nnzh,flag) implicit none C This subroutine might compute the Hessian matrix of the objective C function. For achieving this objective YOU MAY MODIFY it according C to your problem. To modify this subroutine IS NOT MANDATORY. See C below where your modifications must be inserted. C C Parameters of the subroutine: C C On Entry: C C n integer, C number of variables, C C x double precision x(n), C current point, C C On Return C C nnzh integer, C number of perhaps-non-null elements of the computed C Hessian, C C hlin integer hlin(nnzh), C see below, C C hcol integer hcol(nnzh), C see below, C C hval double precision hval(nnzh), C the non-null value of the (hlin(k),hcol(k)) position C of the Hessian matrix of the objective function must C be saved at hval(k). Just the lower triangular part of C Hessian matrix must be computed, C C flag integer, C You must set it to any number different of 0 (zero) if C some error ocurred during the evaluation of the Hessian C matrix of the objective funtion. (For example, trying C to compute the square root of a negative number, C dividing by zero or a very small number, etc.) If C everything was o.k. you must set it equal to zero. C SCALAR ARGUMENTS integer flag,n,nnzh C ARRAY ARGUMENTS integer hcol(*),hlin(*) double precision hval(*),x(n) C ****************************************************************** C FROM HERE ON YOU MAY (OPTIONALY) MODIFY THE SUBROUTINE TO SET THE C HESSIAN MATRIX OF YOUR OBJECTIVE FUNCTION: C ****************************************************************** flag = -1 C ****************************************************************** C STOP HERE YOUR MODIFICATIONS OF SUBROUTINE EVALH. C ****************************************************************** end C ****************************************************************** C ****************************************************************** subroutine evalc(n,x,ind,c,flag) implicit none C This subroutine must compute the i-th constraint of your problem. C For achieving this objective YOU MUST MOFIFY it according to your C problem. See below the places where your modifications must be C inserted. C C Parameters of the subroutine: C C On Entry: C C n integer, C number of variables, C C x double precision x(n), C current point, C C ind integer, C index of the constraint to be computed, C C On Return C C c double precision, C ind-th constraint evaluated at x, C C flag integer C You must set it to any number different of 0 (zero) if C some error ocurred during the evaluation of the C constraint. (For example, trying to compute the square C root of a negative number, dividing by zero or a very C small number, etc.) If everything was o.k. you must set C it equal to zero. C SCALAR ARGUMENTS integer ind,flag,n double precision c C ARRAY ARGUMENTS double precision x(n) C Constraints C ****************************************************************** C FROM HERE ON YOU MUST MODIFY THE SUBROUTINE TO SET YOUR C CONSTRAINTS: C ****************************************************************** flag = -1 C ****************************************************************** C STOP HERE YOUR MODIFICATIONS OF SUBROUTINE EVALC. C ****************************************************************** end C ****************************************************************** C ****************************************************************** subroutine evaljac(n,x,ind,indjac,valjac,nnzjac,flag) implicit none C This subroutine must compute the gradient of the constraint i. For C achieving these objective YOU MUST MODIFY it in the way specified C below. C C Parameters of the subroutine: C C On Entry: C C n integer, C number of variables, C C x double precision x(n), C current point, C C ind integer, C index of the constraint whose gradient will be computed, C C On Return C C nnzjac integer, C number of perhaps-non-null elements of the computed C gradient, C C indjac integer indjac(nnzjac), C see below, C C valjac double precision valjac(nnzjac), C the non-null value of the partial derivative of the i-th C constraint with respect to the indjac(k)-th variable must C be saved at valjac(k). C C flag integer C You must set it to any number different of 0 (zero) if C some error ocurred during the evaluation of the C constraint. (For example, trying to compute the square C root of a negative number, dividing by zero or a very C small number, etc.) If everything was o.k. you must set C it equal to zero. C SCALAR ARGUMENTS integer flag,ind,n,nnzjac C ARRAY ARGUMENTS integer indjac(n) double precision x(n),valjac(n) C Sparse gradient vector of the ind-th constraint C ****************************************************************** C FROM HERE ON YOU MUST MODIFY THE SUBROUTINE TO SET THE GRADIENTS C OF YOUR CONSTRAINTS: C ****************************************************************** flag = -1 C ****************************************************************** C STOP HERE YOUR MODIFICATIONS OF SUBROUTINE EVALJAC. C ****************************************************************** end C ****************************************************************** C ****************************************************************** subroutine evalhc(n,x,ind,hclin,hccol,hcval,nnzhc,flag) implicit none C This subroutine might compute the Hessian matrix of the ind-th C constraint. For achieving this objective YOU MAY MODIFY it C according to your problem. To modify this subroutine IS NOT C MANDATORY. See below where your modifications must be inserted. C C Parameters of the subroutine: C C On Entry: C C n integer, C number of variables, C C x double precision x(n), C current point, C C ind integer, C index of the constraint whose Hessian will be computed, C C On Return C C nnzhc integer, C number of perhaps-non-null elements of the computed C Hessian, C C hclin integer hclin(nnzhc), C see below, C C hccol integer hccol(nnzhc), C see below, C C hcval double precision hcval(nnzhc), C the non-null value of the (hclin(k),hccol(k)) position C of the Hessian matrix of the ind-th constraint must C be saved at hcval(k). Just the lower triangular part of C Hessian matrix must be computed, C C flag integer, C You must set it to any number different of 0 (zero) if C some error ocurred during the evaluation of the Hessian C matrix of the ind-th constraint. (For example, trying C to compute the square root of a negative number, C dividing by zero or a very small number, etc.) If C everything was o.k. you must set it equal to zero. C SCALAR ARGUMENTS integer flag,ind,n,nnzhc C ARRAY ARGUMENTS integer hccol(*),hclin(*) double precision hcval(*),x(n) C ****************************************************************** C FROM HERE ON YOU MAY (OPTIONALY) MODIFY THE SUBROUTINE TO SET THE C HESSIANS OF YOUR CONSTRAINTS: C ****************************************************************** flag = -1 C ****************************************************************** C STOP HERE YOUR MODIFICATIONS OF SUBROUTINE EVALHC. C ****************************************************************** end C ****************************************************************** C ****************************************************************** subroutine evalhlp(n,x,m,lambda,p,hp,goth,flag) implicit none C This subroutine might compute the product of the Hessian of the C Lagrangian times vector p (just the Hessian of the objective C function in the unconstrained or bound-constrained case). C C Parameters of the subroutine: C C On Entry: C C n integer, C number of variables, C C x double precision x(n), C current point, C C m integer, C number of constraints, C C lambda double precision lambda(m), C vector of Lagrange multipliers, C C p double precision p(n), C vector of the matrix-vector product, C C goth logical, C can be used to indicate if the Hessian matrices were C computed at the current point. It is set to .false. C by the optimization method every time the current C point is modified. Sugestion: if its value is .false. C then compute the Hessians, save them in a common C structure and set goth to .true.. Otherwise, just use C the Hessians saved in the common block structure, C C On Return C C hp double precision hp(n), C Hessian-vector product, C C goth logical, C see above, C C flag integer, C You must set it to any number different of 0 (zero) if C some error ocurred during the evaluation of the C Hessian-vector product. (For example, trying to compute C the square root of a negative number, dividing by zero C or a very small number, etc.) If everything was o.k. you C must set it equal to zero. C SCALAR ARGUMENTS logical goth integer flag,m,n C ARRAY ARGUMENTS double precision hp(n),lambda(m),p(n),x(n) flag = - 1 end C ****************************************************************** C ****************************************************************** subroutine endp(n,x,l,u,m,lambda,rho,equatn,linear) implicit none C This subroutine can be used to do some extra job after the solver C has found the solution,like some extra statistics, or to save the C solution in some special format or to draw some graphical C representation of the solution. If the information given by the C solver is enough for you then leave the body of this subroutine C empty. C C Parameters of the subroutine: C C The paraemters of this subroutine are the same parameters of C subroutine inip. But in this subroutine there are not output C parameter. All the parameters are input parameters. C SCALAR ARGUMENTS integer m,n C ARRAY ARGUMENTS logical equatn(m),linear(m) double precision l(n),lambda(m),rho(m),u(n),x(n) C ****************************************************************** C FROM HERE ON YOU MUST MODIFY THE SUBROUTINE TO COMPLEMENT THE C INFORMATION RELATED TO THE SOLUTION GIVEN BY THE SOLVER C ****************************************************************** C ****************************************************************** C STOP HERE YOUR MODIFICATIONS OF SUBROUTINE ENDP C ****************************************************************** end