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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 http://packages.python.org/PuLP/ 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:
a1x1+a2x2 ...anxn (<=, =, >=) b modelling Exported Functions:
construct a linear expression to be used as a constraint or variable [ x1, x2, ..., xn] will construct a linear expression to be used as a constraint or variable Comments, bug reports, patches and suggestions are welcome. pulp-or-discuss@googlegroups.com |