<?xml version="1.0" encoding="UTF-8" ?>
<rdf:RDF xmlns="http://usefulinc.com/ns/doap#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"><Project><name>PuLP</name>
<shortdesc>A Linear Programming modeler</shortdesc>
<description>PuLP is an LP modeler written in python. PuLP can generate MPS or LP 
files and call GLPK[1], COIN CLP/SBB[2], CPLEX[3] and XPRESS[4] to solve
linear problems.

PuLP provides a nice syntax for the creation of linear problems, and a 
simple way to call the solvers to perform the optimization. See the example
below.

This version adds C modules to use the GLPK, COIN and CPLEX solvers without
using intermediate MPS or LP files. It is faster and more reliable.

Multiple examples are provided.

References:
[1] http://www.gnu.org/software/glpk/glpk.html
[2] http://www.coin-or.org/
[3] http://www.cplex.com/
[4] http://www.dashoptimization.com/

Example script:

from pulp import *

prob = LpProblem("test1", LpMinimize)

# Variables
x = LpVariable("x", 0, 4)
y = LpVariable("y", -1, 1)
z = LpVariable("z", 0)

# Objective
prob += x + 4*y + 9*z

# Constraints
prob += x+y &lt;= 5
prob += x+z &gt;= 10
prob += -y+z == 7

GLPK().solve(prob)

# Solution
for v in prob.variables():
   print v.name, "=", v.varValue

print "objective=", value(prob.objective)</description>
<download-page>http://www.jeannot.org/~js/code/pulp-1.1.tgz</download-page>
<homepage rdf:resource="http://www.jeannot.org/~js/code/index.en.html" />
<maintainer><foaf:Person><foaf:name>Jean-Sebastien Roy</foaf:name>
<foaf:mbox_sha1sum>30c83c2bc68c5edf6e979ddf5843d6ad46c516c5</foaf:mbox_sha1sum></foaf:Person></maintainer>
<release><Version><revision>1.1</revision></Version></release>
</Project></rdf:RDF>