CPLEX cpxRetVec

This page is part of the CPLEX Manual. See CPLEX.

Purpose

cpxRetVec is a global variable that CPLEX can write more detailed solution information to. For all fields, the default value is NaN and appears whenever the element in question is not available/not applicable for the problem type.

Note about integer and double quality values:

Some quality values are present in both the integer and double lists. This is because these quality identifiers have a meaning both as double and integer qualities. Example: The double interpretation is normally the largest (absolute) value of the variables, while the integer interpretation is the first index where that value occurs.

Calling Syntax

global cpxRetVec
% Call cplex by tomRun or directly

CPLEX functions or parameter names in cpxRetVec

The following outputs are created:

Index

Result of CPLEX run. (S=Simplex, B=Barrier, MIP=Mixed-Integer) 20 (S,B) Solver method (1 = Primal, 2 = Dual, 4 = Barrier) 1 Solution objective value 2 (MIP) The currently best known bound on the optimal solution value of a MIP problem. When a problem has been solved to optimality, this value matches the optimal solution value. Otherwise, this value is computed for a minimization (maximization) problem as the minimum (maximum) objective function value of all remaining unexplored nodes. 3 (MIP) The MIP cutoff value being used during mixed integer optimization. The cutoff is updated with the objective function value, each time an integer solution is found during branch and cut. 4 (MIP) The node number of the best known integer solution. 7 (MIP) The cumulative number of simplex iterations used to solve a mixed integer problem. 8 (MIP) The number of nodes used to solve a mixed integer problem. 9 (MIP) The number of unexplored nodes left in the branch and cut tree. 5 (S) The total number of simplex iterations to solve an LP problem, or the number of crossover iterations in the case that the barrier optimizer is used. 10 (S,MIP) The number of dual super-basic variables in the current solution. 15 (S,MIP) The number of primal super-basic variables in the current solution. 6 (B) The total number of Barrier iterations to solve an LP problem. 16 (B) The number of dual exchange iterations in the crossover method. An exchange occurs when a nonbasic variable is forced to enter the basis as it is pushed toward a bound. 17 (B) The number of dual push iterations in the crossover method. A push occurs when a nonbasic variable switches bounds and does not enter the basis. 18 (B) The number of primal exchange iterations in the crossover method. An exchange occurs when a nonbasic variable is forced to enter the basis as it is pushed toward a bound. 19 (B) The number of primal push iterations in the crossover method. A push occurs when a nonbasic variable switches bounds and does not enter the basis. 12 (S) The number of Phase I iterations to solve a problem using the primal or dual simplex method. Double-type quality values: 21 The maximum primal infeasibility or, equivalently, the maximum bound violation including slacks for the unscaled problem. 22 The maximum primal infeasibility or, equivalently, the maximum bound violation including slacks for the scaled problem. 23 The sum of primal infeasibilities or, equivalently, the sum of bound violations for the unscaled problem. 24 The sum of primal infeasibilities or, equivalently, the sum of bound violations for the scaled problem. 25 (S,B) The maximum of dual infeasibility or, equivalently, the maximum reduced-cost infeasibility for the unscaled problem. 26 (S,B) The maximum of dual infeasibility or, equivalently, the maximum reduced-cost infeasibility for the scaled problem. 27 (S,B) The sum of dual infeasibilities or, equivalently, the sum of reduced-cost bound violations for the unscaled problem . 28 (S,B) The sum of dual infeasibilities or, equivalently, the sum of reduced-cost bound violations for the scaled problem . 29 (MIP) The maximum of integer infeasibility for the unscaled problem. 30 (MIP) The sum of integer infeasibilities for the unscaled problem. 31 Ax - b\| for the unscaled problem. 32 Ax - b\| for the scaled problem. 33 Ax - b\| for the unscaled problem. 34 Ax - b\| for the unscaled problem. 35 (S,B) The maximum dual residual value. For a simplex solution, this is the maximum of the vector -c-B'pi-, and for a barrier solution, it is the maximum of the vector -A'pi+rc-c- for the unscaled problem. 36 (S,B) The maximum dual residual value for the scaled problem. 37 (S,B) The sum of the absolute values of the dual residual vector for the unscaled problem. 38 (S,B) The sum of the absolute values of the dual residual vector for the scaled problem. 39 (B) The maximum violation of the complementary slackness conditions for the unscaled problem. 41 (B) The sum of the violations of the complementary slackness conditions for the unscaled problem. 43 The maximum absolute value in the primal solution vector for the unscaled problem. 44 The maximum absolute value in the primal solution vector for the scaled problem. 45 (S,B) The maximum absolute value in the dual solution vector for the unscaled problem. 46 (S,B) The maximum absolute value in the dual solution vector for the scaled problem. 47 The maximum absolute slack value for the unscaled problem. 48 The maximum absolute slack value for the scaled problem. 49 (S,B) The maximum absolute reduced cost value for the unscaled problem. 50 (S,B) The maximum absolute reduced cost value for the scaled problem. 51 The sum of the absolute values in the primal solution vector for the unscaled problem. 52 The sum of the absolute values in the primal solution vector for the scaled problem. 53 (S,B) The sum of the absolute values in the dual solution vector for the unscaled problem. 54 (S,B) The sum of the absolute values in the dual solution vector for the scaled problem. 55 The sum of the absolute slack values for the unscaled problem. 56 The sum of the absolute slack values for the scaled problem. 57 (S,B) The sum of the absolute reduced cost values for the unscaled problem. 58 (S,B) The sum of the absolute reduced cost values for the unscaled problem. 59 (S) The estimated condition number of the scaled basis matrix. 60 (B) The objective value gap between the primal and dual objective value solution. 61 (B) The objective value relative to the dual barrier solution. 62 (B) The objective value relative to the primal barrier solution. 81 (MIP) The relative objective gap for a MIP optimization. Integer-type quality values: 63 The lowest index of a column or row where the maximum primal infeasibility occurs for the unscaled problem. 64 The lowest index of a column or row where the maximum primal infeasibility occurs for the scaled problem. 65 (S,B) The lowest index where the maximum dual infeasibility occurs for the unscaled problem. 66 (S,B) the lowest index where the maximum dual infeasibility occurs for the scaled problem. 67 (MIP) The lowest index where the maximum integer infeasibility occurs for the unscaled problem. 68 (MIP) The lowest index where the maximum primal residual occurs for the unscaled problem. 69 (MIP) The lowest index where the maximum primal residual occurs for the scaled problem. 70 (S,B) The lowest index where the maximum dual residual occurs for the unscaled problem. 71 (S,B) The lowest index where the maximum dual residual occurs for the scaled problem 72 (B) The lowest index of a row or column with the largest violation of the complementary slackness conditions. 73 The lowest index where the maximum x value occurs for the unscaled problem. 74 The lowest index where the maximum x value occurs for the scaled problem. 75 (S,B) The lowest index where the maximum pi value occurs for the unscaled problem. 76 (S,B) The lowest index where the maximum pi value occurs for the scaled problem. 77 The lowest index where the maximum slack value occurs for the unscaled problem. 78 The lowest index where the maximum slack value occurs for the scaled problem. 79 (S,B) The lowest index where the maximum reduced cost value occurs for the unscaled problem. 80 (S,B) The lowest index where the maximum reduced cost value occurs for the scaled problem.