SUBROUTINE COBYLA (N,M,X,RHOBEG,RHOEND,IPRINT,MAXFUN,W,IACT,ierr) IMPLICIT DOUBLE PRECISION (A-H,O-Z) DIMENSION X(*),W(*),IACT(*) C C This subroutine minimizes an objective function F(X) subject to M C inequality constraints on X, where X is a vector of variables that has C N components. The algorithm employs linear approximations to the C objective and constraint functions, the approximations being formed by C linear interpolation at N+1 points in the space of the variables. C We regard these interpolation points as vertices of a simplex. The C parameter RHO controls the size of the simplex and it is reduced C automatically from RHOBEG to RHOEND. For each RHO the subroutine tries C to achieve a good vector of variables for the current size, and then C RHO is reduced until the value RHOEND is reached. Therefore RHOBEG and C RHOEND should be set to reasonable initial changes to and the required C accuracy in the variables respectively, but this accuracy should be C viewed as a subject for experimentation because it is not guaranteed. C The subroutine has an advantage over many of its competitors, however, C which is that it treats each constraint individually when calculating C a change to the variables, instead of lumping the constraints together C into a single penalty function. The name of the subroutine is derived C from the phrase Constrained Optimization BY Linear Approximations. C C The user must set the values of N, M, RHOBEG and RHOEND, and must C provide an initial vector of variables in X. Further, the value of C IPRINT should be set to 0, 1, 2 or 3, which controls the amount of C printing during the calculation. Specifically, there is no output if C IPRINT=0 and there is output only at the end of the calculation if C IPRINT=1. Otherwise each new value of RHO and SIGMA is printed. C Further, the vector of variables and some function information are C given either when RHO is reduced or when each new value of F(X) is C computed in the cases IPRINT=2 or IPRINT=3 respectively. Here SIGMA C is a penalty parameter, it being assumed that a change to X is an C improvement if it reduces the merit function C F(X)+SIGMA*MAX(0.0,-C1(X),-C2(X),...,-CM(X)), C where C1,C2,...,CM denote the constraint functions that should become C nonnegative eventually, at least to the precision of RHOEND. In the C printed output the displayed term that is multiplied by SIGMA is C called MAXCV, which stands for 'MAXimum Constraint Violation'. The C argument MAXFUN is an integer variable that must be set by the user to a C limit on the number of calls of CALCFC, the purpose of this routine being C given below. The value of MAXFUN will be altered to the number of calls C of CALCFC that are made. The arguments W and IACT provide real and C integer arrays that are used as working space. Their lengths must be at C least N*(3*N+2*M+11)+4*M+6 and M+1 respectively. C C In order to define the objective and constraint functions, we require C a subroutine that has the name and arguments C SUBROUTINE CALCFC (N,M,X,F,CON) C DIMENSION X(*),CON(*) . C The values of N and M are fixed and have been defined already, while C X is now the current vector of variables. The subroutine should return C the objective and constraint functions at X in F and CON(1),CON(2), C ...,CON(M). Note that we are trying to adjust X so that F(X) is as C small as possible subject to the constraint functions being nonnegative. C C Partition the working space array W to provide the storage that is needed C for the main calculation. C MPP=M+2 ICON=1 ISIM=ICON+MPP ISIMI=ISIM+N*N+N IDATM=ISIMI+N*N IA=IDATM+N*MPP+MPP IVSIG=IA+M*N+N IVETA=IVSIG+N ISIGB=IVETA+N IDX=ISIGB+N IWORK=IDX+N CALL COBYLB (N,M,MPP,X,RHOBEG,RHOEND,IPRINT,MAXFUN,W(ICON), 1 W(ISIM),W(ISIMI),W(IDATM),W(IA),W(IVSIG),W(IVETA),W(ISIGB), 2 W(IDX),W(IWORK),IACT, ierr) RETURN END