Now it is possible to declare, in a MILP problem in text format, all variables as belonging to a specific type
using the "ALL" statement (for example, if all variables are wanted to be integers "INT ALL").
It is also possible, still in text format, to declare in a MILP problem a subset of variables as belonging to a
specific type using the wildcard statement "*" (see example 2.9).
In text format, it is now possible to explicitly specify constraints by placing variables on both the left-hand side (LHS) and right-hand side (RHS).
Furthermore, in text format, it is not necessary to include all variables in the objective function, but only those with coefficients different from zero.
It is possible to provide a problem in text format by inserting it into a string (see example 1.5 ).
Finally, in problems with text format stored in external files, it is no longer possible to pass a simple path as a string to the constructor,
but rather as an instance of the Path class (see example 1.11 ).
Warning, The library now has prefixes related to the package names that have been changed from it.ssc to org.ssclab
to ensure uniqueness by aligning these names with the domain name made available on the internet. Nevertheless, the class
names and their functionalities remain the same as in previous versions.
Additionally, this version introduces several improvements in memory usage.
From this version it is possible to interrupt the simplex or the B&B to obtain a
feasible solution that is not necessarily optimal (see examples 1.10
and 2.14).
Starting from version 3, in the problems with matrix format, the "Double" wrapper is no longer used
to store the coefficients of the matrix A and the rhs values, but the "double" primitive is used.
As a result, the null values cannot be stored in these variables, but will be represented
with the NaN notation (see example 1.4). Furthermore, the inequalities format has been
modified to be more flexible (see example 1.6). Finally, in the use of the sparse format it
is necessary to pass to the LP (or MILP) constructor the constant FormatType.SPARSE
(see example 1.7)
SSC4.2.0r0.jar.zip
SSC4.2.0r0.src.zip
Git Hub
Now it is possible to declare, in a MILP problem in text format, all variables as belonging to a specific type using the "ALL" statement (for example, if all variables are wanted to be integers "INT ALL"). It is also possible, still in text format, to declare in a MILP problem a subset of variables as belonging to a specific type using the wildcard statement "*" (see example 2.9).
SSC4.1.0r1.jar.zip
SSC4.1.0r1.src.zip
Optimization of cleaning the final table Phase 1 of the simplex.
SSC4.1.0r0.jar.zip
SSC4.1.0r0.src.zip
In text format, it is now possible to explicitly specify constraints by placing variables on both the left-hand side (LHS) and right-hand side (RHS). Furthermore, in text format, it is not necessary to include all variables in the objective function, but only those with coefficients different from zero. It is possible to provide a problem in text format by inserting it into a string (see example 1.5 ). Finally, in problems with text format stored in external files, it is no longer possible to pass a simple path as a string to the constructor, but rather as an instance of the Path class (see example 1.11 ).
SSC4.0.0r0.jar.zip
SSC4.0.0r0.src.zip
Warning, The library now has prefixes related to the package names that have been changed from it.ssc to org.ssclab to ensure uniqueness by aligning these names with the domain name made available on the internet. Nevertheless, the class names and their functionalities remain the same as in previous versions. Additionally, this version introduces several improvements in memory usage.
SSC3.0.1r3.jar.zip
SSC3.0.1r3.src.zip
SSC3.0.1r0.jar.zip
SSC3.0.1r0.src.zip
From this version it is possible to interrupt the simplex or the B&B to obtain a feasible solution that is not necessarily optimal (see examples 1.10 and 2.14).
SSC3.0.0r2.jar.zip
Starting from version 3, in the problems with matrix format, the "Double" wrapper is no longer used to store the coefficients of the matrix A and the rhs values, but the "double" primitive is used. As a result, the null values cannot be stored in these variables, but will be represented with the NaN notation (see example 1.4). Furthermore, the inequalities format has been modified to be more flexible (see example 1.6). Finally, in the use of the sparse format it is necessary to pass to the LP (or MILP) constructor the constant FormatType.SPARSE (see example 1.7)