英文:
Cplex optimization program returns results equal to zero
问题
我目前正在解决一个优化问题，其中一个湖有150单位的水。我每卖出一单位的水就得到3美元，但我需要保证月底时还剩下100单位的水，否则我就要为低于100单位的每一单位支付5美元。我知道雨水会带来125单位的水（稍后我会添加随机性的降雨）。
我的模型如下：
!pip install cplex
!pip install docplex
from docplex.mp.model import Model
from docplex.mp.environment import Environment
env = Environment()
env.print_information()
mdl = Model()
x = mdl.continuous_var(lb=None, ub=None, name=None )
y = mdl.continuous_var(lb=None, ub=None, name=None )
r1=mdl.add_constraint( 150-x+y+125 >= 100 )
s = mdl.solve()
mdl.maximize( 3*x-5*y )
obj = mdl.objective_value
print(x.solution_value)
print(y.solution_value)
print("* best objective is: {:g}".format(obj))
mdl.export("modelo_determinista_bajo.lp")
其中x是卖出的水量，y是低于100单位的水量。
模型的输出对于x、y和收益都是零。
我看不出我做错了什么。有人可以帮帮我吗？
致以最诚挚的问候。
英文:
I am currently working on an optimization problem in which a lake has 150 units of water. I am paid 3$ for each unit of water sold, but I need to guarantee that 100 units of water will remain at the end of the month or pay 5$ for each unit below the threshold of 100. I know that rain will bring 125 units of water (later on I will add stochastic rain).
My model is as follows
!pip install cplex
!pip install docplex
from docplex.mp.model import Model
from docplex.mp.environment import Environment
env = Environment()
env.print_information()
mdl = Model()
x = mdl.continuous_var(lb=None, ub=None, name=None )
y = mdl.continuous_var(lb=None, ub=None, name=None )
r1=mdl.add_constraint( 150-x+y+125 >= 100 )
s = mdl.solve()
mdl.maximize( 3*x-5*y )
obj = mdl.objective_value
print(x.solution_value)
print(y.solution_value)
print("* best objective is: {:g}".format(obj))
mdl.export("modelo_determinista_bajo.lp")
where x is the amount of water sold and y is the amount of water below the 100 units mark.
The output of the model is zero for x, y and the benefit.
I cannot see what I am doing wrong. Can someone help me?
Best regards.
答案1
得分: 1
from docplex.mp.model import Model
from docplex.mp.environment import Environment
env = Environment()
env.print_information()
mdl = Model()
x = mdl.continuous_var(lb=None, ub=None, name=None )
y = mdl.continuous_var(lb=None, ub=None, name=None )
r1=mdl.add_constraint( 150-x+y+125 >= 100 )
mdl.maximize( 3*x-5*y )
s = mdl.solve()
obj = mdl.objective_value
print(x.solution_value)
print(y.solution_value)
print("* best objective is: {:g}".format(obj))
mdl.export("modelo_determinista_bajo.lp")
英文:
from docplex.mp.model import Model
from docplex.mp.environment import Environment
env = Environment()
env.print_information()
mdl = Model()
x = mdl.continuous_var(lb=None, ub=None, name=None )
y = mdl.continuous_var(lb=None, ub=None, name=None )
r1=mdl.add_constraint( 150-x+y+125 >= 100 )
mdl.maximize( 3*x-5*y )
s = mdl.solve()
obj = mdl.objective_value
print(x.solution_value)
print(y.solution_value)
print("* best objective is: {:g}".format(obj))
mdl.export("modelo_determinista_bajo.lp")
gives
175.0
0
* best objective is: 525
答案2
得分: 0
-
Model.maximize()（或者minimize()）简单地_设置_目标和方向，但不运行solve()，因此不会计算出（新的）解决方案。 -
默认情况下，目标值为0，这并不像看起来那么愚蠢：CPLEX将尝试找到一个_可行的_解决方案。如果成功，目标值当然等于0。
-
在调用
mdl.solve()之前调用mdl.objective_value将导致运行时错误：没有解决方案存在，因此该属性为空，并且会引发异常；这很可能是你遇到的情况。实际上，你应该会得到一个DOcplexException：docplex.mp.utils.DOcplexException: Model<docplex_model1>尚未解决
英文:
To complement Alex's code:
-
Model.maximize()(resp. minimize()) simply sets the objective and sense, but does not run solve(), therefore no (new) solution is computed. -
By default, the objective is 0, which is not as silly as it may seem: CPLEX
will try to find a feasible solution. If it succeeds, the objective value equals (of course) 0. -
Calling
mdl.objective_valuebeforemdl.solve()will cause a runtime error: no solution is present, so the attribute is empty, and an exception is raised; this is likely what you have encountered.
You should get actually aDOcplexException:docplex.mp.utils.DOcplexException: Model<docplex_model1> has not been solved yet
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