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Objective¶

using `summation`¶

model.coeffs = Param(model.set_i, model.set_j, default=1) 
def obj_rule(model):
    return summation(model.coeffs, model.x)
model.obj = Objective(rule=obj_rule, sense=maximize)

using expression¶

def obj_rule(model):
    expr = 0
    for i in model.I:
        for j in model.J:
            expr += log(model.x[i,j]) + model.x[i,j]**2
    return expr

using index¶

def obj_rule(model, i, j):
    if i == j:
        return Objective.Skip
    else:
      return 2 * model.x[i,j]
model.obj = Objective(model.set_i, model.set_j, rule=obj_rule, sense=minimize)

update objective¶

m.obj = Objective(expr=m.x)
m.obj.set_value(expr=m.o.expr + m.e)

m.obj_base = m.x1 + 2 * m.x2, 
m.obj_changing = m.x1 * m.x2, 
m.obj.set_value(expr=m.base_expr + m.changing_expr)

add a term to objective¶

import pyomo.environ as pyo

# create model and var
m = pyo.ConcreteModel()
m.x = pyo.Var(within=pyo.NonNegativeReals)

# create obj
@m.Objective()
def obj(m):
    return 0  # must add a placeholder via expr. will not work `model.obj = pyo.Objective(sense=pyo.minimize)` without `expr=0`
m.obj.pprint()

# add a term
m.obj += m.x**2
m.obj.pprint()