pyepo.model.copt.coptmodel
==========================

.. py:module:: pyepo.model.copt.coptmodel

.. autoapi-nested-parse::

   Abstract optimization model based on Cardinal Optimizer (COPT)



Classes
-------

.. autoapisummary::

   pyepo.model.copt.coptmodel.optCoptModel


Module Contents
---------------

.. py:class:: optCoptModel

   Bases: :py:obj:`pyepo.model.opt.optModel`


   Abstract base class for Cardinal Optimizer (COPT) backed models.

   Subclasses implement ``_getModel`` to build a COPT ``Model`` and return
   ``(model, variables)``. The objective sense is auto-detected from the
   underlying COPT model (no need to set ``modelSense`` manually); solver
   logging is silenced by default. Cost-vector updates use the C-level
   ``setInfo("Obj", ...)`` batch path for efficiency. A process-local COPT
   ``Envr`` singleton is reused across instances to avoid re-booting the
   license and worker threads on every model build.

   :ivar _model: underlying COPT model

   :vartype _model: coptpy.Model


   .. py:method:: setObj(c: numpy.ndarray | torch.Tensor | list) -> None

      A method to set the objective function

      :param c: cost of objective function



   .. py:method:: solve() -> tuple[numpy.ndarray, float]

      A method to solve the model

      :returns: optimal solution and objective value
      :rtype: tuple



   .. py:method:: copy() -> Self

      A method to copy the model

      :returns: new copied model
      :rtype: optModel



   .. py:method:: addConstr(coefs: numpy.ndarray | torch.Tensor | list, rhs: float) -> Self

      A method to add a new constraint

      :param coefs: coefficients of new constraint
      :param rhs: right-hand side of new constraint

      :returns: new model with the added constraint
      :rtype: optModel