Determines whether the optimizer should attempt to branch on general split disjunctions during the branch and bound search.
Specifies how cautious or aggressive the optimizer should be when searching for and applying conflict cuts. Conflict cuts are in-tree cuts derived from nodes found to be infeasible or cut off, which can be used to cut off other branches of the search tree.
A flags enum providing detailed control of the cuts created for the root node of a global solve. Use TREECUTSELECT to control cuts during the tree search.
The cut strategy. Used to specify the cut intensity during tree search.
WARNING: Make sure to not accidentally select the default-value of this enum, which is NoCuts/0, instead of the defined default value of FICO, which is Automatic/-1.
This specifies the dual simplex pricing method. Refers to: http://www.maths.ed.ac.uk/hall/Xpress/FICO_Docs/optimizer/HTML/DUALGRADIENT.html
Enum to change the emphasis of the diving heuristic from solution quality to diving speed.
Enum for selecting which local search heuristics to apply on the root node of a global solve. Use HeuristicSearchTreeSelections to control local search heuristics during the tree search. Default: LargeNeighborhood | SearchUserAddedSolutions (= 17).
The local search heuristics will benefit from having an existing incumbent solution, but it is not required. An initial solution can also be provided by the user through either XPRSloadmipsol or XPRSreadbinsol. Refers to: http://www.maths.ed.ac.uk/hall/Xpress/FICO_Docs/optimizer/HTML/HEURSEARCHROOTSELECT.html
Enum for selecting which local search heuristics to apply on the root node of a global solve. Use HeuristicSearchRootSelections to control local search heuristics on the root node Default: SmallNeighborhoodContinuous (= 1).
The local search heuristics will benefit from having an existing incumbent solution, but it is not required. An initial solution can also be provided by the user through either XPRSloadmipsol or XPRSreadbinsol. Refers to: http://www.maths.ed.ac.uk/hall/Xpress/FICO_Docs/optimizer/HTML/HEURSEARCHTREESELECT.html
This specifies the heuristic strategy. On some problems it is worth trying more comprehensive heuristic strategies by setting HeuristicStrategy to Enhanced or Extensive. Refers to: http://www.maths.ed.ac.uk/hall/Xpress/FICO_Docs/optimizer/HTML/HEURSTRATEGY.html
How to update the pseudo cost for a global entity when a strong branch or a regular branch is applied.
Controls when to perform a local backtrack between the two child nodes during a dive in the branch and bound tree.
Specifies how often the optimizer should run a heuristic to reduce the number of fractional integer variables in the node LP solutions.
This heuristic is only applicable to problems that are dual degenerate. These are problems that contain multiple solutions with identical objective function value. The more dual degenerate a problem is, the more likely it will be for this heuristic to have an improving effect. Refers to: http://www.maths.ed.ac.uk/hall/Xpress/FICO_Docs/optimizer/HTML/MIPFRACREDUCE.html
Type of integer processing to be performed.
Presolve: Specifies whether the optimizer should attempt to recombine constraints in order to reduce the number of non zero coefficients when presolving a mixed integer problem.
Amount of probing to perform on binary variables during presolve. This is done by fixing a binary to each of its values in turn and analyzing the implications.
Enum to control presolve modes at the beginning of the solution process.
Determines if presolving should be performed on the problem after the global search has finished with root cutting and heuristics.
This determines how the Optimizer will rescale a model internally before optimization. If set to 0, no scaling will take place. NOTE: Setting SCALING to 0 will preserve the current scaling of the problem. Refer to: http://www.maths.ed.ac.uk/hall/Xpress/FICO_Docs/optimizer/HTML/SCALING.html
Adjusts the overall amount of effort for symmetry detection.
This determines the formula used to calculate the estimate of each integer variable, and thus which integer variable is selected to be branched on at a given node. The variable selected to be branched on is the one with the maximum estimate.