CPLEX 11

CPLEX 11 25epint (real)Integrality Tolerance. This specifies the amount by which an integer variable can be different than an integerand still be considered feasible.Range: [0,0.5](default = 1e-005)epmrk (real)The Markowitz tolerance influences pivot selection during basis factorization. Increasing the Markowitzthreshold may improve the numerical properties of the solution.Range: [0.0001,0.99999](default = 0.01)epopt (real)The optimality tolerance influences the reduced-cost tolerance for optimality. This option setting governshow closely Cplex must approach the theoretically optimal solution.Range: [1e-009,0.1](default = 1e-006)epper (real)Perturbation setting. Highly degenerate problems tend to stall optimization progress. Cplex automaticallyperturbs the variable bounds when this occurs. Perturbation expands the bounds on every variable by asmall amount thereby creating a different but closely related problem. Generally, the solution to the lessconstrained problem is easier to solve. Once the solution to the perturbed problem has advanced as far asit can go, Cplex removes the perturbation by resetting the bounds to their original values.If the problem is perturbed more than once, the perturbation constant is probably too large. Reduce theepper option to a level where only one perturbation is required. Any value greater than or equal to 1.0e-8is valid.(default = 1e-006)eprhs (real)Feasibility tolerance. This specifies the degree to which a problem’s basic variables may violate their bounds.This tolerance influences the selection of an optimal basis and can be reset to a higher value when a problemis having difficulty maintaining feasibility during optimization. You may also wish to lower this toleranceafter finding an optimal solution if there is any doubt that the solution is truly optimal. If the feasibilitytolerance is set too low, Cplex may falsely conclude that a problem is infeasible.Range: [1e-009,0.1](default = 1e-006)feasopt (integer)With Feasopt turned on, a minimum-cost relaxation of the right hand side values of constraints or boundson variables is computed in order to make an infeasible model feasible. It marks the relaxed right hand sidevalues and bounds in the solution listing.Several options are available for the metric used to determine what constitutes a minimum-cost relaxationwhich can be set by option feasoptmode.Feasible relaxations are available for all problem types with the exception of quadratically constraint problems.(default = 0)0 Turns Feasible Relaxation off1 Turns Feasible Relaxation on