Glpk java 输出

Glpk java output

如何在我的控制台或文件上打印 java-glpk 中所有已解决的问题?

像这样: (此输出来自 gusek)

------ ------------    ------------- ------------- -------------
     1 x[1]         *              1             0             1 
     2 x[2]         *              1             0             1 
     3 x[3]         *              0             0             1 
     4 x[4]         *              1             0             1 
     5 x[5]         *              1             0             1 
     6 x[6]         *              1             0             1 

我的 java 代码中的听众(GlpkCallback.addListener(this) 和 GlpkTerminal.addListener(this))只是 return this:

GLPK Integer Optimizer, v4.55
3 rows, 15440 columns, 46320 non-zeros
15440 integer variables, all of which are binary
Preprocessing...
1 row, 15440 columns, 15440 non-zeros
15440 integer variables, all of which are binary
Scaling...
 A: min|aij| = 5.718e+001  max|aij| = 2.719e+005  ratio = 4.755e+003
GM: min|aij| = 1.000e+000  max|aij| = 1.000e+000  ratio = 1.000e+000
EQ: min|aij| = 1.000e+000  max|aij| = 1.000e+000  ratio = 1.000e+000
2N: min|aij| = 6.701e-001  max|aij| = 1.330e+000  ratio = 1.985e+000
Constructing initial basis...
Size of triangular part is 1
Solving LP relaxation...
GLPK Simplex Optimizer, v4.55
1 row, 15440 columns, 15440 non-zeros
*     0: obj =  1.584183802e+007  infeas = 0.000e+000 (0)
*   500: obj =  1.190189187e+007  infeas = 0.000e+000 (0)
*  1000: obj =  1.142465659e+007  infeas = 0.000e+000 (0)
*  1500: obj =  1.122247777e+007  infeas = 0.000e+000 (0)
*  1615: obj =  1.121676854e+007  infeas = 0.000e+000 (0)
OPTIMAL LP SOLUTION FOUND
Integer optimization begins...
+  1615: mip =     not found yet >=              -inf        (1; 0)
+  1615: >>>>>  1.121676854e+007 >=  1.121676854e+007   0.0% (1; 0)
Better solution found
+  1615: mip =  1.121676854e+007 >=     tree is empty   0.0% (0; 1)
INTEGER OPTIMAL SOLUTION FOUND

希望有人能提供帮助。

这是我的 java 代码: https://jsfiddle.net/ilucasrds/enok1h5k/3/

在示例中,您展示了两种不同的东西。 一方面,听众的输出包含求解器 运行 时提供的所有信息。另一方面,gusek 示例在求解器完成后提供了解决方案。

根据您想要的解决方案的信息类型,API 有四种不同的例程供您选择:

int glp_print_sol(glp_prob *P, const char *fname);
int glp_print_ipt(glp_prob *P, const char *fname);
int glp_print_mip(glp_prob *P, const char *fname);

对于 KKT-Conditions(simplex/interiorpoint) 和整数可行性报告。

int glp_print_ranges(glp prob *P, int len, const int list[], int flags,
const char *fname);

写敏感度分析报告,与gusek输出相当。使用附加的 len 和 list[] 属性,可以定义一组更具体的 rows/cols 到 analyse/output。如果 len 为零,则分析每个 row/col。

对于解决方案的进一步代码处理,也可以使用

double glp_get_obj_coef(glp_prob *P, int j);

这将 return 定义列的 objective 系数