Purpose
 
 
  Fixes all the
 
 MIP entities to the values of the last found MIP solution. This is useful for finding the
 
reduced costs for the continuous variables after the integer variables have been fixed to their optimal values.
 
 Topic areas
 
  
  Synopsis
 
 
 int XPRS_CC XPRSfixmipentities(XPRSprob prob, int options);
 
 
 FIXMIPENTITIES [-flags]
 
 
  Arguments
 
 
 
  
   | 
     prob 
     | 
     The current problem.
     | 
  
   | 
     options 
     | 
      Options how to fix the MIP entities.
      
      
       
        | 
          Bit
          | 
          Meaning
          |  
        | 
          0 
          | 
          If all MIP entities should be rounded to the nearest discrete value in the solution before being fixed.
          |  
        | 
          1 
          | 
          If piecewise linear and general constraints should be kept in the problem with only the non-convex decisions (i.e. which part of a non-convex piecewise linear function or which variable attains a maximum) fixed. Otherwise all variables appearing in piecewise linear or general constraints will be fixed.
          |  | 
  
   | 
     flags 
     | 
     Flags to pass to FIXMIPENTITIES:
     
     
      
       | 
         r 
         | 
         round all MIP entities to the nearest feasible value in the solution before being fixed;
         |  
       | 
         t 
         | 
         keep piecewise linear and general constraints and only fix their non-convex decisions.
         |  | 
 
 
  Example 1 (Library)
 
 
 This example performs a tree search on problem
 myprob and then uses
 XPRSfixmipentities before solving the remaining linear problem:
 
 
 XPRSreadprob(prob,"myprob","");
XPRSmipoptimize(prob," ");
XPRSfixmipentities(prob, 1);
XPRSlpoptimize(prob," ");
XPRSwriteprtsol(prob);
  
  Example 2 (Console)
 
 
 A similar set of commands at the console would be as follows:
 
 
 READPROB
MIPOPTIMIZE
FIXMIPENTITIES -r
LPOPTIMIZE
PRINTSOL
  
  Further information
 
 
 1. Because of tolerances, it is possible for e.g. a binary variable to be slightly fractional in the MIP solution, where it might have the value
 0.999999 instead of being at exactly
 1.0. With
 ifround = 0, such a binary will be fixed at
 0.999999, but with
 ifround = 1, it will be fixed at
 1.0.
 
 
 2. This command is useful for inspecting the reduced costs of the continuous variables in a matrix after the MIP entities have been fixed.
 
Sensitivity analysis can also be performed on the continuous variables in a MIP problem using
 
XPRSrhssa,
 
XPRSobjsa or
 
XPRSbndsa after calling
 
XPRSfixmipentities (
 
FIXMIPENTITIES).
 
 3. For nonlinear problems, one can set the initial point to the solution returned by the MIP search (via
 XPRSnlpsetcurrentiv) and then call
 XPRSfixmipentitiesand reoptimize the problem using a local solver (
 XPRSnlpoptimize). to obtain an approximation of the dual values
 
 
  Related topics
 
 
                 
                
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