Question

我正在使用pyomo处理LP模型，但是当我创建约束时，它显示了一个关键错误“找不到特定组合”。我知道列出所有组合都可以解决此问题。但是实际数据有很多组合。有什么简单的方法可以解决这种问题？谢谢！这是一个简单的例子：

这是一个类似的问题，可供参考： Is there an easier way to avoid this kind of index key error of pyomo?

from pyomo.environ import *
import pandas as pd 
data = [['tom','A', 10], ['nick','A', 15], ['juli','B',14]]
df = pd.DataFrame(data, columns = ['Name','Type', 'Age'])  
#set
A = set(df['Name'])
B = set(df['Type'])
model = ConcreteModel()
#parameter
C= df.set_index(['Name','Type'])['Age'].to_dict()
#varibale
model.AB = Var(A,B,domain = NonNegativeReals)
#constraint1
def cons1(model,a,b):
    return(model.AB[a,b]<=C[a,b])
model.Cons1 = Constraint(A,B,rule = cons1)
#constraint2
def cons2(model,a):
    return(sum(model.AB[a,b]<=C[a,b] for b in B)<=1)
model.Cons2 = Constraint(A,rule = cons2)

Answer 1

从your previous question中给出的解决方案开始，并修正第二个约束中我认为是错别字的方法，诀窍是检查何时（a，b）对在集合IJ中总和遍历B：

from pyomo.environ import *
import pandas as pd 
data = [['tom','A', 10], ['nick','A', 15], ['juli','B',14], ['juli','A',14]]
df = pd.DataFrame(data, columns = ['Name','Type', 'Age'])  
#set
A = set(df['Name'])
B = set(df['Type'])
model = ConcreteModel()
#parameter
C= df.set_index(['Name','Type'])['Age'].to_dict()
#varibale
model.IJ = Set(initialize=C.keys())
model.AB = Var(model.IJ,domain = NonNegativeReals)
#constraint1
def cons1(model,a,b):
    return(model.AB[a,b]<=C[a,b])
model.Cons1 = Constraint(model.IJ,rule = cons1)

def cons2(model,a):
    return(sum(model.AB[a,b] for b in B if (a,b) in model.IJ)<=1)
model.Cons2 = Constraint(A,rule = cons2)

在pyomo中处理此类关键错误的最佳方法是什么？

1 个答案: