Gurobi变量self.a与self.b返回0.0，如何获取其正确值？

The main problems with your code are that you're not creating a valid constraint involving your variables, and you haven't defined an objective function for Gurobi to optimize. Here's how to resolve this:

Breakdown of the Issues #

1. Invalid Constraint: In your constraint1 method, you're overwriting the variable references (lhs1 and rhs1) with integers 2 and 3, which results in a trivial constraint (2 <= 3) that doesn't affect your variables at all. Your variables end up with no meaningful constraints beyond their lower bound of 0.
2. Missing Objective Function: Without an objective (something to maximize or minimize), Gurobi just returns any feasible solution. Since your variables only have a lower bound of 0, it defaults to that value.

Corrected Code #

from gurobipy import GRB, Model

class abc(object):
    def __init__(self):
        self.model = Model()

    def creatingvarriables(self):
        # Add variables (model.update() is not required here; addVar handles it automatically)
        self.a = self.model.addVar(lb=0, vtype=GRB.CONTINUOUS, name="y_")
        self.b = self.model.addVar(lb=0, vtype=GRB.CONTINUOUS, name="q_")
        
        # Define an objective function (example: maximize the sum of a and b)
        self.model.setObjective(self.a + self.b, GRB.MAXIMIZE)

    def constraint1(self):
        # Create a valid constraint using your variables (adjust this to match your actual needs)
        # Example: 2*a <= 3*b
        self.model.addConstr(2 * self.a, GRB.LESS_EQUAL, 3 * self.b, name="constraint1")

    def printvalues(self):
        # Run optimization
        self.model.optimize()
        
        # Check if optimization succeeded before accessing values
        if self.model.status == GRB.OPTIMAL:
            print(self.a.X)
            print(self.b.X)
        else:
            print("Optimization did not find an optimal solution.")

if __name__ == "__main__":
    newobject = abc()
    newobject.creatingvarriables()
    newobject.constraint1()
    newobject.printvalues()

Key Fixes #

• Valid Constraint: We now build a constraint using the actual variables instead of overwriting references. Adjust the constraint expression to match your specific problem requirements (e.g., self.a <= 2 or self.b >= 3).
• Objective Function: Added setObjective to give Gurobi a clear goal (here, maximizing the sum of a and b). Modify this to your desired objective (minimize, maximize, or a custom linear expression).
• Status Check: Added a check for GRB.OPTIMAL to handle cases where optimization might fail (e.g., infeasible model).

Once these changes are applied, Gurobi will compute the optimal values for your variables based on your defined objective and constraints.

内容的提问来源于stack exchange，提问作者Danial Jalil