My favorites | Sign in
Project Logo
Project hosting will be READ-ONLY Wednesday at 8am PST due to brief network maintenance.
                
Show all Featured wiki pages:
OptimisationWithPuLP
People details
Project owners:
  stuvagas
Project committers:
vanyasim...@yahoo.com

PuLP is an LP modeler written in python. PuLP can generate MPS or LP files and call GLPK (http://www.gnu.org/software/glpk/glpk.html), COIN (http://www.coin-or.org/), CPLEX (http://www.cplex.com/), and GUROBI (http://www.gurobi.com/) to solve linear problems.

See the examples directory for examples.

PuLP requires Python >= 2.5.

The examples require at least a solver in your PATH or a shared library file.

Documentation is found on https://www.coin-or.org/PuLP/.

A comprehensive wiki can be found at https://www.coin-or.org/PuLP/ While in transition other documentation can be found http://code.google.com/p/pulp-or/wiki/OptimisationWithPuLP or http://130.216.209.237/engsci392/pulp/OptimisationWithPuLP

Use LpVariable() to create new variables. To create a variable 0 <= x <= 3

>>> x = LpVariable("x", 0, 3)

To create a variable 0 <= y <= 1

>>> y = LpVariable("y", 0, 1)

Use LpProblem() to create new problems. Create "myProblem"

>>> prob = LpProblem("myProblem", LpMinimize)

Combine variables to create expressions and constraints and add them to the problem.

>>> prob += x + y <= 2

If you add an expression (not a constraint), it will become the objective.

>>> prob += -4*x + y

Choose a solver and solve the problem. ex:

>>> status = prob.solve(GLPK(msg = 0))

Display the status of the solution

>>> LpStatus[status]
'Optimal'

You can get the value of the variables using value(). ex:

>>> value(x)
2.0

Exported Classes:

Exported Functions:

Comments, bug reports, patches and suggestions are welcome.

pulp-or-discuss@googlegroups.com









Hosted by Google Code