if model.status == GRB.OPTIMAL: print('Optimal solution found:') print('Objective value:', model.objVal) print('Variable value:', x.x) else: print('Optimization problem is infeasible or unbounded') 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19...
Variable Attributes 变量属性 例如: X 当前变量的取值; Start MIP初始解。 Linear Constraint Attributes 线性约束属性 例如: Pi 约束对应的对偶值;Slack 约束的松弛量;RHS 约束的右端项。 Special-ordered Set constraints Attributes SOS约束属性
print("x:", result.get_variable_value("x")) print("y:", result.get_variable_value("y")) print("z:", result.get_variable_value("z")) ``` 运行上述代码后,Gurobi 将根据给定的限制条件求解问题,并输出最优解。 5.总结 Gurobi 是一种强大的数学优化软件,支持多种限制条件。通过与 Python 结...
Python 提供了各种方法来操作列表，这是最常用的数据结构之一。使用列表时的一项常见任务是计算其中唯一值...
#print('Demand',Demand) # 提取Depot和取送货点的最早和最晚取送货时间及时间窗 TimeWindow={} EarliestTime=TaskData.sort_values(by='ET').iloc[0,3] LatestTime=TaskData.sort_values(by='LT',ascending=False).iloc[0,4] for i in range(nrows): ...
value(x[i]),sol.value(y[i]))) print(f"radius: {sol.value(r)}") print("="*15) for i in range(num_circles): print(f"location circle {i}") print(f"x: {circle_loc[i][0]}") print(f"y: {circle_loc[i][1]}") print("="*15) figure, axes = plt.subplots(1, figsize=...
print(figurine.x) print(horn.x) print(cider.x) 运行示例将为你提供以下输出: Optimize a model with 1 rows, 4 columns and 4 nonzeros Variable types: 0 continuous, 4 integer (4 binary) Coefficient statistics: Matrix range [2e+00, 1e+01] ...
除了获取变量的最优值之外,`getvalue()`函数还可以用于获取其他信息,例如变量的上下界、约束条件的最优对偶变量等。具体而言,我们可以使用`getAttr()`函数获取变量的其他属性。 python #获取变量上下界 lb = x.getAttr(GRB.Attr.LB) ub =x.getAttr(GRB.Attr.UB) print("Variable bounds:") print("lb =",...
-2: removed, -1: not in model, otherwise: index of the variable in the model Example: v=model.getVars()[0]print(v.index)# Index will be 0 setAttr(attrname,newvalue)# Set the value of a variable attribute. Note that, due to our lazy update approach, the change won’t actually ...
(variable or equation).feaspref(value) For example, suppose we have a GAMS declaration: Set i /i1*i5/; Set j /j2*j4/; variable v(i,j); equation e(i,j); Then, the relaxation preference in the gurobi.opt file can be specified by: feasopt 1 v.feaspref 1 v.feaspref('i1...