A — Vector of length N. (Input)
See B.

B — Real vector of length N. (Input)
A and B define the rectangular region in which the points will be generated, i.e., A(I) < S(I) < B(I) for I = 1, 2, …, N. Note that if B(I) < A(I), then B(I) < S(I) < A(I).

K — The number of points to be generated. (Input)

IDO — Initialization parameter. (Input/Output)
IDO must be set to zero for the first call. GGUES resets IDO to 1 and returns the first generated point in S. Subsequent calls should be made with IDO = 1.

S — Vector of length N containing the generated point. (Output)
Each call results in the next generated point being stored in S.

N — Dimension of the space. (Input)
Default: N = SIZE (B,1).

1. Workspace may be explicitly provided, if desired, by use of G2UES/DG2UES. The reference is:

2. Informational error

3. The routine GGUES may be used with any nonlinear optimization routine that requires starting points. The rectangle to be searched (defined by A, B, and N) must be determined; and the number of starting points, K, must be chosen. One possible use for GGUES would be to call GGUES to generate a point in the chosen rectangle. Then, call the nonlinear optimization routine using this point as an initial guess for the solution. Repeat this process K times. The number of iterations that the optimization routine is allowed to perform should be quite small (5 to 10) during this search process. The best (or best several) point(s) found during the search may be used as an initial guess to allow the optimization routine to determine the optimum more accurately. In this manner, an N dimensional rectangle may be effectively searched for a global optimum of a nonlinear function. The choice of K depends upon the nonlinearity of the function being optimized. A function with many local optima requires a larger value than a function with only a few local optima.