pyomo_linear_programming_maximize_objective_with_glpk_solver.py

1import pyomo.environ as pyo
2
3# Create a model
4model = pyo.ConcreteModel()
5
6# Declare decision variables
7model.x = pyo.Var(domain=pyo.NonNegativeReals)
8model.y = pyo.Var(domain=pyo.NonNegativeReals)
9
10# Declare objective
11model.obj = pyo.Objective(expr=2*model.x + 3*model.y, sense=pyo.maximize)
12
13# Declare constraints
14model.constraint1 = pyo.Constraint(expr=3*model.x + 4*model.y <= 1)
15
16# Solve the model (requires a solver like glpk, ipopt, or cbc installed on your system)
17solver = pyo.SolverFactory('glpk')
18results = solver.solve(model)
19
20# Display results
21model.display()