文件名称:miosqp:基于OSQP的MIQP求解器
文件大小:828KB
文件格式:ZIP
更新时间:2024-06-11 18:14:48
optimization branch-and-bound miqp-solver Python
基于OSQP的混合整数二次程序求解器 miOSQP解决了以下形式的混合整数二次程序(MIQP) minimize 0.5 x' P x + q' x subject to l <= A x <= u x[i] in Z for i in i_idx i_l[i] <= x[i] <= i_u[i] for i in i_idx 其中i_idx是索引的向量,其变量是整数, i_l , i_u分别是整数变量的下限和上限。 安装 要安装该软件包,只需运行 python setup.py install 它取决于 ,numpy和scipy。 用法 要解决MIQP,我们需要运行 import miosqp m = miosqp . MIOSQP () m . setup ( P , q , A , l ,
【文件预览】:
miosqp-master
----max_iter_examples()
--------32.pickle(59KB)
--------41.pickle(58KB)
--------37.pickle(59KB)
--------55.pickle(58KB)
--------70.pickle(58KB)
--------61.pickle(58KB)
--------57.pickle(58KB)
--------52.pickle(58KB)
--------36.pickle(59KB)
--------39.pickle(58KB)
--------68.pickle(58KB)
--------46.pickle(59KB)
--------38.pickle(58KB)
--------50.pickle(58KB)
--------45.pickle(58KB)
--------30.pickle(59KB)
--------59.pickle(58KB)
--------65.pickle(58KB)
--------69.pickle(58KB)
--------74.pickle(58KB)
--------58.pickle(58KB)
--------67.pickle(58KB)
--------43.pickle(58KB)
--------34.pickle(59KB)
--------53.pickle(58KB)
--------56.pickle(58KB)
--------73.pickle(58KB)
--------51.pickle(58KB)
--------54.pickle(58KB)
--------76.pickle(19KB)
--------33.pickle(59KB)
--------40.pickle(58KB)
--------42.pickle(58KB)
--------44.pickle(58KB)
--------47.pickle(58KB)
--------60.pickle(58KB)
--------62.pickle(58KB)
--------63.pickle(58KB)
--------31.pickle(59KB)
--------35.pickle(59KB)
--------64.pickle(58KB)
--------29.pickle(59KB)
--------75.pickle(58KB)
--------48.pickle(58KB)
--------49.pickle(58KB)
--------28.pickle(59KB)
--------71.pickle(58KB)
--------72.pickle(58KB)
--------66.pickle(58KB)
----miosqp()
--------node.py(4KB)
--------workspace.py(13KB)
--------data.py(3KB)
--------__init__.py(99B)
--------results.py(372B)
--------solver.py(6KB)
--------constants.py(231B)
----examples()
--------random_miqp()
--------__init__.py(0B)
--------power_converter()
----LICENSE(11KB)
----setup.py(509B)
----README.md(3KB)
----.gitignore(1KB)
----run_examples.py(277B)
----extra()
--------run_maxiter_problem.py(974B)