Question

我有一些基于成本的供应链管理代码，其中供应尝试满足需求，但这仅在供应大于需求时才有效。我有什么办法可以优化它使其同时工作（例如，在supply > demand和supply < demand时）？

from pyomo.core import *
model = AbstractModel()
model.warehouses = Set()
model.stores = Set()
model.supply = Param(model.warehouses)
model.demand = Param(model.stores)
model.costs = Param(model.warehouses, model.stores)
model.amounts = Var(model.warehouses, model.stores, 
within=NonNegativeReals)

def costRule(model):
   return sum(
      model.costs[n,i]
      for n in model.warehouses
      for i in model.stores
)

model.cost=Objective(rule=costRule)

def minDemandRule(model, store):
    return sum(model.amounts[i, store] for i in model.warehouses) >= 
model.demand[store]

model.demandConstraint = Constraint(model.stores, rule=minDemandRule)

def maxSupplyRule(model, warehouse):
    return sum(model.amounts[warehouse, j] for j in model.stores) <= 
model.supply[warehouse]

model.supplyConstraint = Constraint(model.warehouses, rule=maxSupplyRule)

我的输入：

set warehouses := hyd ban coh;
set stores := cbe mdu cnr whc whe;
param: supply :=
hyd   10
ban   10
coh   10;
param: demand :=
cbe    5
mdu    5
cnr    5
whc    5
whe    5;
param costs:
      cbe mdu cnr whc whe:=
hyd    1   3    2   2    1
ban    4   5    1   1    3
coh    2   3    3   2    1;

这里supply = 30和demand = 25。它有效，我得到的输出是变量：

amounts[ban,cbe]:
    Value: 5
amounts[ban,whc]:
    Value: 5
amounts[coh,whe]:
    Value: 5
amounts[hyd,cnr]:
    Value: 5
amounts[hyd,mdu]:
  Value: 5

但是，当供应量少于需求量时，它就不起作用。这里supply = 30和demand = 40：

param: supply :=
hyd   10
ban   10
coh   10;
param: demand :=
cbe    5
mdu    5
cnr    5
whc    5
whe    20;
param costs:
      cbe mdu cnr whc whe:=
hyd    1   3    2   2    1
ban    4   5    1   1    3
coh    2   3    3   2    1;

我需要以下期望的输出：变量：

amounts[ban,cbe]:
  Value: 5
amounts[ban,whc]:
  Value: 5
amounts[coh,whe]:
  Value: 10
amounts[hyd,cnr]:
  Value: 5
amounts[hyd,mdu]:
  Value: 5

 whe_demand =10

Answer 1

由于约束model.demandConstraint，当需求大于供应时，您的模型似乎不可行。装运数量不能满足需求，因为否则将违反其他约束model.supplyConstraint。

如果要对缺乏需求满意度的情况进行惩罚，则可以为相关约束定义松弛变量，并将这些条件添加到目标中。

这本书可能是您的理想资源：https://www.wiley.com/en-us/Model+Building+in+Mathematical+Programming%2C+5th+Edition-p-9781118443330

PYOMO优化以满足供需<需求

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