I would like to announce the release of PuLP v 1.1. 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. You can get it at: http://www.jeannot.org/~js/code/pulp-1.1.tgz The latest version is always available at: http://www.jeannot.org/~js/code/index.en.html Multiple examples are provided. Thanks, Jean-Sebastien 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 <= 5 prob += x+z >= 10 prob += -y+z == 7 GLPK().solve(prob) # Solution for v in prob.variables(): print v.name, "=", v.varValue print "objective=", value(prob.objective)