Python Gurobi：如何在目标函数中实现决策变量的最大值？

Question

Hopefully someone can help me out. I am developing an optimization model where I minimize electricity costs over time ( t ) and over different transactions ( s ). (where: standard power( p )*costs of electricity ( c ) = electricity costs).

Now I am trying to implement a cost component in the objective function that is based on the maximum power consumption that occurred (some alike: max(P[s,t]) ). However, np.max() returns an error because P[s,t] is an unsupported class for np.max(). Also the Gurobi function gp.max_(P[s,t]) also gives an unsupported class error. Is there someone who has a solution?

Code:

obj = gp.quicksum(p[s, t] * Cost_elect[t]e for t in range(T) for s in range(S)) + gp.max_(p_batt_ch[s,t]*fixed_cost for t in range(T) for s in range(S))

Answer 1

You need to assign the max constraint to a new auxiliary variable and the put this variable into the objective instead of the actual constraint.

maxobj = model.addVar()
max_constr = model.addConstr(maxobj == gp.max_(p_batt_ch[s,t] * fixed_cost
                             for t in range(T) for s in range(S)))

obj = gp.quicksum(p[s,t] * Cost_elect[t] for t in range(T) for s in range(S)) + maxobj)

Gurobi documentation