问题标签 [scip]
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windows - Scip 与 mingw 和 msys 集成
如何将 SCIP 与 MinGW 和 Msys 集成?
linear-programming - 意外的 VARSYM、ZIMPL 程序
我的 ZIMPL 程序出现意外的 VARSYM 错误,我不知道问题出在哪里,这是代码的一部分
这里是变量
上升到 28,其中一些点的上限为 3、2 和 1
这是得到错误的方程
错误说它在分号的末尾
scip - SCIP 无法读取我的输入
我正在尝试使用 SCIP 求解器(http://scip.zib.de/)。我的输入 ( 1.lp
) 是lpsolve
格式。它看起来像这样:
我像这样运行 SCIP:
但是,SCIP 会生成以下输出:
我想这意味着它在空白处窒息......我做错了什么?
编辑:
有关详细信息,请参阅我的答案。以 CPLEX 格式提供输入后,一切正常。
scip - 使用 SCIP 获得最佳可行解决方案
我正在使用SCIP (SoPlex)来解决由 .mps 文件提供的 MIP(混合整数程序)。我通过命令行使用 SCIP,如下所示:
我不想有一个不可行的解决方案——想要最好的可行方案。供您参考:我将 CPLEX 与相同的文件一起使用,它确认存在一个最佳可行解决方案,其 obj 值稍差(例如差 0.05 %)。我已经尝试过强调可行性,SCIP> set emphasis feasibility
但这对我没有帮助——你自己看看:
亲切的问候。
编辑:为了回应用户 mattmilten 的回答,我不得不分享set numerics feastol 1e-9
单独使用并没有带来可行的解决方案,但是使用较低的容差,例如1e-10
与 结合使用set emphasis feasibility
,SCIP 能够提供一个很好的可行解决方案,仅差 0.005%比CPLEX'。
感谢您的帮助 mattmilten!
matrix - Scip 可以根据矩阵方程求解 MIP 吗?
我的问题涉及 Scip 中的混合整数编程(MIP):
我有以下代码:
由于矩阵约束是线性的,因此可以将方程转换为线性方程组(通过克罗内克积和矢量化操作),但这仅限于小 n。是否可以直接用 Scip 求解矩阵方程?有没有办法嵌入外部求解器?还是我必须为连续的 lyapunov 矩阵方程编写自己的求解器?
linear-programming - LP relaxation in SCIP
I'm trying to solve a MIP using the SCIP command line, with the problem input in CPLEX LP format. However, due to large number of variables, the optimization is taking a lot of time. Is there some way to compute the LP Relaxtion solution of the same MIP in SCIP?
Or any other way to get an approximate, somewhat suboptimal solution?
scip - 运行 SCIP 的示例之一时出错
我在 SCIP 包中运行 VRP 示例时遇到问题,我按照此链接中提供的说明进行操作:http: //scip.zib.de/doc/html/START.php
但是当我在创建的 VRP 目录中运行“make”时,出现以下错误:No rule to make target ../../src/objscip/objscip.h', needed by
obj/O.linux.x86_64.gnu.opt/main_vrp.o'。停止。
有人能帮助我吗?
scip - 在 SCIP 中指定包含两个变量相乘的约束的最佳方法是什么?
我在我的 c++ 代码中使用 SCIP Optimization Suite 3.0.2 来实现调度程序,我想问你实现约束的最佳方法是什么,例如:
t_i*p + d*p + t_i <=0
其中t_i
是连续变量,p
是二进制变量,d
是常数。我找到了所有支持的约束类型的概述:scip 约束,并且我以某种方式将我的问题实现为更线性约束以及它们之间的连接和分离的层次结构,但我有一个怀疑,这使得寻找解决方案变得困难。因此,如果有更直接的方法,我很感兴趣,特别是对于两个变量的乘法。
scip - SCIP unmodified LP-bound
I am using SCIP 3.0.2 with cplex 12.6 as LP-solver. My model requires Column generation. I already implemented it in CPLEX but since CPLEX can only do CG in the root node I am using SCIP to do Branch-and-Price. In CPLEX it turned out to be beneficial to turn off heursitics, cuts and preprocessing/probing. I set the following in SCIP:
My parameter-file looks as follows:
To check that the models are the same I solved the CPLEX model in SCIP (without CG) and I obtained the same LP-bound as for the model generated with SCIP but different from the LP-bound when solving with CPLEX.
It seems that SCIP is still using some 'magic' I have not deactivated yet. So my question is what do I have to deactivate to obtain an LP-bound relying just on my model.
I already took a look at the statistics out-put and there are indeed some things that might help to solve the problem:
- Constraints #EnfoLP lists 1 for integral (seems strange since cuts are disabled?)
- The transformed problem seems to be ok. The statistics-output prints:
Presolved Problem : Problem name : t_ARLP Variables : 969 (806 binary, 0 integer, 0 implicit integer, 163 continuous) Constraints : 9311 initial, 9311 maximal
and before the iterations start I get the following:
LP Solver : row representation of the basis not available -- SCIP parameter lp/rowrepswitch has no effect transformed problem has 897 variables (806 bin, 0 int, 0 impl, 91 cont) and 9311 constraints
9311 constraints of type < linear >
presolving: presolving (0 rounds): 0 deleted vars, 0 deleted constraints, 0 added constraints, 0 tightened bounds, 0 added holes, 0 changed sides, 0 changed coefficients 0 implications, 0 cliques presolved problem has 897 variables (806 bin, 0 int, 0 impl, 91 cont) and 9311 constraints
9311 constraints of type < linear >
Presolving Time: 0.00
I added 72 columns: 91 original +72 added = 163 total. This seems to be ok.
I added the suggested parameters. It seems that domain propagation has not been in use before but there has been strong branching. Unfortunately nothing changed with the parameters.
In addition to adding the parameters I also tried to use SCIP 3.0.1 instead. This improved my bound from 670.194 to 699.203 but this is still quite different from the cplex bound with 754.348. I know that the solvers differ by a lot of numerical parameters but I guess the difference is too large to be caused by these parameters?