COPT#

Cardinal Optimizer (COPT) incorporates a full suite of solvers for linear, convex quadratic, and second-order conic mixed-integer programming. It ranks at the top of benchmark tests on continuous linear programs, and has been fully extended to handle integer variables. The framework used by the driver supports automatic reformulation for many expression types; the modeling guide can be found here.

Product Page | Modeling guide | Features guide | Options | Changes

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How to use it#

How to install using amplpy:

# Install Python API for AMPL:
$ python -m pip install amplpy --upgrade

# Install AMPL & solver modules:
$ python -m amplpy.modules install copt # install COPT

# Activate your license (e.g., free ampl.com/ce or ampl.com/courses licenses):
$ python -m amplpy.modules activate <your-license-uuid>

How to use:

from amplpy import AMPL
ampl = AMPL()
...
ampl.solve(solver="copt", copt_options="option1=value1 option2=value2")

Learn more about what we have to offer to implement and deploy Optimization in Python.

AMPL APIs are interfaces that allow developers to access the features of the AMPL interpreter from within a programming language. We have APIs available for:

ampl: option solver copt; # change the solver
ampl: option copt_options 'option1=value1 option2=value2'; # specify options
ampl: solve; # solve the problem

Resources#

Solver options#

Full list of solver options:

More details on solver options: Features guide.

Retrieving solutions#

The outcome of the last optimization is stored in the AMPL parameter solve_result_num and the relative message in solve_result.

display solve_result_num, solve_result;

COPT solve result codes can be obtained by running copt -! or ampl: shell "copt -!";:

Solve result table for COPT 7.1.3
	  0- 99	solved: optimal for an optimization problem,
		feasible for a satisfaction problem 
	100-199	solved? solution candidate returned but error likely 
	    150	solved? MP solution check failed (option sol:chk:fail) 
	200-299	infeasible 
	300-349	unbounded, feasible solution returned 
	350-399	unbounded, no feasible solution returned 
	400-449	limit, feasible: stopped, e.g., on iterations or Ctrl-C 
	450-469	limit, problem is either infeasible or unbounded.
		Disable dual reductions or run IIS finder for definitive answer.
	470-499	limit, no solution returned 
	500-999	failure, no solution returned 
	    550	failure: numeric issue, no feasible solution

For general information, see MP result codes guide.

Changelog#