在典型的运输优化问题中,我们对给定的来源(配送中心)和需求(商店)点进行成本优化
在下面的示例中,我们如何添加附加约束以限制配送中心(DC)的数量
即。 问题:
if dc_lim=10
total_available_DCs=30
Then Total DCs in optimize network<=dc_lim.
当前代码:
model = ConcreteModel()
model.dual = Suffix(direction=Suffix.IMPORT)
# Step 1: Define index sets
CUS = list(I) # Stores
SRC = list(Supply.keys()) # DCs (Distribution Centres)
K=list(Products)
# Step 2: Define the decision
model.x = Var(CUS, SRC,K, domain = NonNegativeReals)
# Step 3: Define Objective
model.Cost = Objective(
expr = sum([T[c,s,k]*model.x[c,s,k] for c in CUS for s in SRC for k in K if (c,s,k) in T]),
sense = minimize)
# Step 4: Constraints
#Supply Constraint
model.src = ConstraintList()
for s in SRC:
model.src.add(sum([model.x[c,s,k] for c in CUS for k in K if (c,s,k) in T]) <= Supply[s])
#Demand Constraint
model.dmd = ConstraintList()
for c in CUS:
for k in K:
model.dmd.add(sum([model.x[c,s,k] for s in SRC if (c,s,k) in T]) == Demand[c,k])
results = SolverFactory('glpk').solve(model)
最好是看数学,而不是一堆代码。我们开始吧
将其转录成代码是微不足道的
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