TOMLAB OPTIMIZATION ENVIRONMENT: probAssign

probAssign

Purpose

For setting up a most types of problems.

Syntax

   Prob = probAssign(optType, x_L, x_U, Name, x_0, fLowBnd, ...
                     A, b_L, b_U, c_L, c_U, x_min, x_max, f_opt, x_opt);

Description

probAssign implements the TOMLAB Quick (TQ) format for most types of optimization.

However, there are a number of specialized routines for different types:

When the type is lp or qp, lpAssign and qpAssign are recommended
For mip mipAssign must be used.
For glc glcAssign should be used if there any integer constraints
For glb either probAssign or glcAssign could be used.
For ls/cls clsAssign is strongly recommended
For uc/con conAssign is recommended. The pattern of the Hessian (or the constraint gradient matrix) could then be given, and the routine names are directly given, without the extra call to mFiles.

probAssign is setting the variables normally needed for an optimization in the TOMLAB structure Prob.

An additional call to mFiles.m is needed to set names of functions used:

   Prob = mFiles(Prob, .....)

optType is one of the optimization problem types defined in TOMLAB

Input Parameters

Call with at least four parameters

 optType Any of lp,uc,qp,con,ls,cls,glb,glc
         For lp,  better to use lpAssign instead
         For qp,  better to use qpAssign instead
         For mip, you must use mipAssign instead
         For glc, you should use glcAssign if there are integer constraints
         For glb, you could use glcAssign instead
         For ls/cls,  better to use clsAssign instead
         For uc/con,  conAssign has expanded functionality
 x_L     Lower bounds on parameters x. If [] set as a nx1 -Inf vector.
 x_U     Upper bounds on parameters x. If [] set as a nx1  Inf vector.
 Name    The name of the problem (string
 x_0     Starting values, default nx1 zero vector 

 Note:   The number n of the unknown variables x are taken as
         max(length(x_L),length(x_U),length(x_0))
         You must specifiy at least one of these with correct length,
         then the others are given default values

         The following parameters are optional, and problem type dependent
         Set empty to get default value

 fLowBnd A lower bound on the function value at optimum. Default -realmax.
         A good estimate is not critical. Use [] if not known at all.

 A       Matrix A in linear constraints b_L<=A*x<=b_U. Stored dense or sparse.
 b_L     Lower bound vector in linear constraints b_L<=A*x<=b_U. 
 b_U     Upper bound vector in linear constraints b_L<=A*x<=b_U. 
 c_L     Lower bound vector in nonlinear constraints b_L<=c(x)<=b_U. 
 c_U     Upper bound vector in nonlinear constraints b_L<=c(x)<=b_U. 
         c(x) must be defined in a function, see e.g. con_c.m
 x_min   Lower bounds on each x-variable, used for plotting
 x_max   Upper bounds on each x-variable, used for plotting
 f_opt   Optimal function value(s), if known (Stationary points)
 x_opt   The x-values corresponding to the given f_opt, if known.
         If only one f_opt, give x_opt as a 1 by n vector
         If several f_opt values, give x_opt as a length(f_opt) by n matrix
         If adding one extra column n+1 in x_opt, 0 is min, 1 saddle, 2 is max.
         x_opt and f_opt is used in printouts and plots.

Set the variable as empty if this variable is not needed for the particular kind of problem you are solving

simAssign

mFiles