If you instead set the PoolGap parameter to value 0.2, the MIP solver would discard any solutions whose objective value is worse than 120 (which would also leave 3 solutions in the solution pool). If you set the PoolSearchMode parameter to 2 and the PoolSolutions parameter to 10, the ...
You can also add an ABS constraint using the abs_ function. Parameters: resvar –(Var) The variable whose value will be to equal the absolute value of the argument variable. argvar –(Var) The variable for which the absolute value will be taken. name –(string, optional) Name for the...
Maximum value: Infinity Terminates as soon as the engine determines that the best bound on the objective value is at least as good as the specified value. Optimization returns with an USER_OBJ_LIMIT status in this case. Note that you should always include a small tolerance in this value. Wi...
Maximum matrix coefficient (in absolute value) in the linear constraint matrix. For examples of how to query or modify attributes, refer to our Attribute Examples.MinCoeff Type: double Modifiable: No Minimum non-zero matrix coefficient (in absolute value) in the linear constraint matrix. For exam...
If provided, this value specifies the absolute objective degradation when doing hierarchical multi-objective optimization. The default value is 0. name (optional) Specified via model.multiobj(i).name. If provided, this string specifies the name of the i-th objective function. Note that when ...
This argument can be NULL, in which case the constraint is given a default name. resvar –The index of the resultant variable r whose value will be to equal the absolute value of the argument variable. argvar –The index of the argument variable x for which the absolute value will be ...
This argument can be NULL, in which case the constraint is given a default name. resvar –The index of the resultant variable r whose value will be to equal the absolute value of the argument variable. argvar –The index of the argument variable x for which the absolute value will be ...