PuLP is an LP modeler written in python. PuLP can generate MPS or LP files and call GLPK, COIN CLP/CBC, CPLEX and XPRESS to solve linear problems.

A comprehensive wiki can be found at http://130.216.209.237/engsci392/pulp/OptimisationWithPuLP

Use LpVariable() to create new variables. ex: x = LpVariable("x", 0, 3) to create a variable 0 <= x <= 3

Use LpProblem() to create new problems. ex: prob = LpProblem("myProblem", LpMinimize)

Combine variables to create expressions and constraints and add them to the problem. ex: prob += x + y <= 2 If you add an expression (not a constraint, f.e. prob += 4*z + w), it will become the objective.

Choose a solver and solve the problem. ex: prob.solve(GLPK())

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

Exported Classes:

• LpProblem -- Container class for a Linear programming problem
• LpVariable -- Variables that are added to constraints in the LP
• LpConstraint -- A constraint of the general form

a1x1+a2x2 ...anxn (<=, =, >=) b

• LpConstraintVar -- Used to construct a column of the model in column-wise

modelling

Exported Functions:

• value() -- Finds the value of a variable or expression
• lpSum() -- given a list of the form [a1*x1, a2x2, ..., anxn] will construct

a linear expression to be used as a constraint or variable

• lpDot() --given two lists of the form [a1, a2, ..., an] and

[ x1, x2, ..., xn]will construct a linear expression to be used as a constraint or variable