README.md

Simplex Algorithm

The simplex package contained in this repository provides an interface for constructing linear programs and solving them with the Simplex algorithm.

Usage

Consider the following LP:

Maximize 3x + 4y subject to the following constraints:

x + 2y ≤ 14

3x - y ≥ 0

x - y ≤ 2

The code below demonstrates how to construct and solve this LP using the simplex package.

For simplicity, this solver assumes that the objective is to be maximized and does not provide the option to set explicit lower bounds on variables.

from simplex import Solver

# Create the solver
solver = Solver()

# Create variables
x = solver.add_variable('x', Solver.INFINITY)
y = solver.add_variable('y', Solver.INFINITY)

# Constraint 0: x + 2y <= 14.
constraint0 = solver.add_constraint(-Solver.INFINITY, 14)
constraint0.set_coefficient(x, 1)
constraint0.set_coefficient(y, 2)

# Constraint 1: 3x - y >= 0.
constraint1 = solver.add_constraint(0, Solver.INFINITY)
constraint1.set_coefficient(x, 3)
constraint1.set_coefficient(y, -1)

# Constraint 2: x - y <= 2.
constraint2 = solver.add_constraint(-Solver.INFINITY, 2)
constraint2.set_coefficient(x, 1)
constraint2.set_coefficient(y, -1)

# Objective function: 3x + 4y.
objective = solver.objective()
objective.set_coefficient(x, 3)
objective.set_coefficient(y, 4)

# Solve the linear program
status = solver.solve()

print('Solution status:', status)
print('Objective value:', objective.solution_value)
print('x value:', x.solution_value)
print('y value:', y.solution_value)