Formulate optimization problems using sympy expressions and solve them using interfaces to third-party optimization software (e.g. GLPK).
Project description
optlang
Vision
optlang provides a common interface to a series of optimization solvers (linear & non-linear) and relies on sympy for problem formulation (constraints, objectives, variables, etc.). Adding new solvers is easy: just sub-class the high-level interface and implement the necessary solver specific routines.
Installation
Install using pip
pip install optlang
Local installations like
python setup.py install
might fail installing the dependencies (unresolved issue with easy_install). Running
pip install -r requirements.txt
beforehand should fix this issue.
Documentation
The documentation for optlang is provided at readthedocs.org.
Dependencies
Example
Formulating and solving the problem is straightforward (example taken from GLPK documentation):
from optlang import Model, Variable, Constraint, Objective x1 = Variable('x1', lb=0) x2 = Variable('x2', lb=0) x3 = Variable('x3', lb=0) c1 = Constraint(x1 + x2 + x3, ub=100) c2 = Constraint(10 * x1 + 4 * x2 + 5 * x3, ub=600) c3 = Constraint(2 * x1 + 2 * x2 + 6 * x3, ub=300) obj = Objective(10 * x1 + 6 * x2 + 4 * x3, direction='max') model = Model(name='Simple model') model.objective = obj model.add([c1, c2, c3]) status = model.optimize() print "status:", model.status print "objective value:", model.objective.value for var_name, var in model.variables.iteritems(): print var_name, "=", var.primal
The example will produce the following output:
status: optimal objective value: 733.333333333 x2 = 66.6666666667 x3 = 0.0 x1 = 33.3333333333
Future outlook
Gurobi interface (very efficient MILP solver)
CPLEX interface (very efficient MILP solver)
Mosek interface (provides academic licenses)
GAMS output (support non-linear problem formulation)
DEAP (support for heuristic optimization)
Interface to NEOS optimization server (for testing purposes and solver evaluation)
Automatically handle fractional and absolute value problems when dealing with LP/MILP/QP solvers (like GLPK, CPLEX etc.)
Requirements
Project details
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