问题描述
我在 PYOMO 中使用 SCIP 求解器（带有 AMPL 可执行文件）来解决优化问题。不幸的是，.sol 格式的输出文件不包含迭代数据。解决方案文件中可用的信息如下所示。
SCIP version 6.0.0 [precision: 8 byte] [memory: block] [mode: optimized] [LP solver: SoPlex 4.0.0] [GitHash: 77d3bc8]
copyright (C) 2002-2018 Konrad-Zuse-Zentrum fuer informationstechnik Berlin (ZIB)
External codes:
SoPlex 4.0.0 Linear Programming Solver developed at Zuse Institute Berlin (soplex.zib.de) [GitHash: 82cab95]
CppAD 20180000.0 Algorithmic Differentiation of C++ algorithms developed by B. Bell (www.coin-or.org/CppAD)
Ipopt 3.12.12 Interior Point Optimizer developed by A. Waechter et.al. (www.coin-or.org/Ipopt)
ASL AMPL Solver Library developed by D. Gay (www.netlib.com/ampl)
RNING: unkNown parameter <output_file>
number of parameters = 2428
non-default parameter settings:
read problem <C:\Users\Wilson\AppData\Local\Temp\tmp1sfv6ovn.pyomo.nl>
============
original problem has 5 variables (0 bin,0 int,0 impl,5 cont) and 3 constraints
solution violates original bounds of variable <_svar[1]> [1,3] solution value <0>
all 1 solutions given by solution candidate storage are infeasible
presolving:
(round 1,fast) 0 del vars,0 del conss,0 add conss,5 chg bounds,0 chg sides,0 chg coeffs,0 upgd conss,0 impls,0 clqs
(round 2,2 add conss,0 clqs
(round 3,4 upgd conss,0 clqs
(round 4,fast) 1 del vars,1 del conss,9 chg bounds,0 clqs
presolving (5 rounds: 5 fast,1 medium,1 exhaustive):
1 deleted vars,1 deleted constraints,2 added constraints,9 tightened bounds,0 added holes,0 changed sides,0 changed coefficients
0 implications,0 cliques
presolved problem has 6 variables (0 bin,6 cont) and 4 constraints
1 constraints of type <abspower>
3 constraints of type <quadratic>
Presolving Time: 0.00
time | node | left |LP iter|LP it/n| mem |mdpt |frac |vars |cons |cols |rows |cuts |confs|strbr| dualbound | primalbound | gap
* 0.0s| 1 | 0 | 9 | - | 587k| 0 | - | 6 | 4 | 6 | 13 | 0 | 0 | 0 | 2.000000e+00 | 2.000000e+00 | 0.00%
0.0s| 1 | 0 | 9 | - | 587k| 0 | - | 6 | 4 | 6 | 13 | 0 | 0 | 0 | 2.000000e+00 | 2.000000e+00 | 0.00%
SCIP Status : problem is solved [optimal solution found]
Solving Time (sec) : 0.01
Solving Nodes : 1
Primal Bound : +1.99999999998750e+00 (1 solutions)
Dual Bound : +1.99999999998750e+00
Gap : 0.00 %
optimal solution found
但是这个输出不包含迭代数据。使用IPOPT求解器的迭代数据示例如下所示。
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
0 2.5371030e+001 1.20e+002 1.11e+001 -1.0 0.00e+000 - 0.00e+000 0.00e+000 0
1 2.5059090e+001 1.09e+002 1.36e+001 -1.0 1.38e+002 - 9.86e-001 9.10e-002h 1
2 2.5312561e+001 9.68e-003 4.92e-001 -1.0 1.11e+002 - 1.00e+000 1.00e+000h 1
3 2.5056729e+001 1.15e-002 4.98e-002 -1.7 2.90e+000 - 1.00e+000 1.00e+000f 1
4 2.5006568e+001 5.10e-004 2.25e-003 -2.5 7.21e-001 - 1.00e+000 1.00e+000h 1
有什么办法可以使用 SCIP 求解器获得此类数据？如果有人有想法，请告诉我。谢谢。
解决方法
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