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| |1||Solution objective value | | |1||Solution objective value |
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| |2||(MIP) The currently best known bound on the optimal solution value of a MIP prob- lem. When a problem has been solved to optimality, this value matches the optimal solution value. Otherwise, this value is computed for a minimization (maximiza- tion) problem as the minimum (maximum) objective function value of all remaining unexplored nodes. | | |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. | | |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. |
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| |38||(S,B) The sum of the absolute values of the dual residual vector for the scaled problem. | | |38||(S,B) The sum of the absolute values of the dual residual vector for the scaled problem. |
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| |39||(B) The maximum violation of the complementary slackness conditions for the un- scaled problem. | | |39||(B) The maximum violation of the complementary slackness conditions for the unscaled problem. |
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| |41||(B) The sum of the violations 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. |
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| |44||The maximum absolute value in the primal solution vector for the scaled problem. | | |44||The maximum absolute value in the primal solution vector for the scaled problem. |
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| |45||(S,B) The maximum absolute value in the dual solution vector for the unscaled prob- lem. | | |45||(S,B) The maximum absolute value in the dual solution vector for the unscaled problem. |
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| |46||(S,B) The maximum absolute value in the dual solution vector for the scaled problem. | | |46||(S,B) The maximum absolute value in the dual solution vector for the scaled problem. |
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| |62||(B) The objective value relative to the primal barrier solution. | | |62||(B) The objective value relative to the primal barrier solution. |
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| | |81||(MIP) The relative objective gap for a MIP optimization. |
| |} | | |} |
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| |66||(S,B) the lowest index where the maximum dual infeasibility occurs for the scaled problem. | | |66||(S,B) the lowest index where the maximum dual infeasibility occurs for the scaled problem. |
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| |67||(MIP) The lowest index where the maximum integer infeasibility occurs for the un- scaled problem. | | |67||(MIP) The lowest index where the maximum integer infeasibility occurs for the unscaled problem. |
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| |68||(MIP) The lowest index where the maximum primal residual occurs for the unscaled problem. | | |68||(MIP) The lowest index where the maximum primal residual occurs for the unscaled problem. |
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| |80||(S,B) The lowest index where the maximum reduced cost value occurs for the scaled problem. | | |80||(S,B) The lowest index where the maximum reduced cost value occurs for the scaled problem. |
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| |81||(MIP) The relative objective gap for a MIP optimization.
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| |} | | |} |
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This page is part of the CPLEX Manual. See CPLEX.
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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.
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6 |
(B) The total number of Barrier iterations to solve an LP problem.
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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.
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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.
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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.
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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.
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Double-type quality values:
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The maximum primal infeasibility or, equivalently, the maximum bound violation including slacks for the unscaled problem.
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22 |
The maximum primal infeasibility or, equivalently, the maximum bound violation including slacks for the scaled problem.
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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.
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30 |
(MIP) The sum of integer infeasibilities for the unscaled problem.
|
31 |
Ax - b\| for the unscaled problem.
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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.
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36 |
(S,B) The maximum dual residual value for the scaled problem.
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37 |
(S,B) The sum of the absolute values of the dual residual vector for the unscaled problem.
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38 |
(S,B) The sum of the absolute values of the dual residual vector for the scaled problem.
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39 |
(B) The maximum violation of the complementary slackness conditions for the unscaled problem.
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41 |
(B) The sum of the violations of the complementary slackness conditions for the unscaled problem.
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43 |
The maximum absolute value in the primal solution vector for the unscaled problem.
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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.
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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.
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53 |
(S,B) The sum of the absolute values in the dual solution vector for the unscaled problem.
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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.
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56 |
The sum of the absolute slack values for the scaled problem.
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57 |
(S,B) The sum of the absolute reduced cost values for the unscaled problem.
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58 |
(S,B) The sum of the absolute reduced cost values for the unscaled problem.
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59 |
(S) The estimated condition number of the scaled basis matrix.
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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.
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62 |
(B) The objective value relative to the primal barrier solution.
|
81 |
(MIP) The relative objective gap for a MIP optimization.
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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.
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