我正在尝试将几个lpSum表达式连接成一个长表达式,这将是我的目标函数。然而,我试图以一种优雅的方式合并这些表达式,导致了不想要的结果。
我想要这样的东西:
a = pulp.lpSum(...)
b = pulp.lpSum(...)
c = pulp.lpSum(...)
prob += a + b - c我的代码更加具体:
alloc_prob = pulp.LpProblem("Supplier Allocation Problem", pulp.LpMinimize)
TPC_func = pulp.lpSum(X[s][p]*procCosts[s][p] for s in supplier for p in
project), "Total Procurement Costs"
TTC_func = pulp.lpSum(X[s][p]*transCosts[s][p] for s in supplier for p in
project), "Total Transportation Costs (incl. taxes/duties)"
TD_func = pulp.lpSum(X_SEP[c][1]*discountFactor['Bonus / ton [€/t]'][c] for
c in company), "Total Discounts"`
# Objective function: TPC + TTC - TD -> min
alloc_prob += TPC_func + TTC_func - TD_func我已经尝试过不同的嵌套方法,例如:
prob += [pulp.lpSum(X[s][p]*procCosts[s][p] + X[s][p]*transCosts[s][p] for s
in supplier for p in project) - pulp.lpSum(X_SEP[c][1]*discountFactor['Bonus
/ ton [€/t]'][c] for c in company)]输出做了它应该做的事情。然而,这既不是一个很好的代码,也不能分配给目标函数。有没有一种聪明的实现方式?
谢谢!
发布于 2019-01-17 04:49:30
在看不到错误的情况下,我可以100%确定,但我认为您在lpsum中包含的名称导致了问题,请尝试以下操作
alloc_prob = pulp.LpProblem("Supplier Allocation Problem", pulp.LpMinimize)
TPC_func = pulp.lpSum(X[s][p]*procCosts[s][p] for s in supplier for p in
project)
TTC_func = pulp.lpSum(X[s][p]*transCosts[s][p] for s in supplier for p in
project)
TD_func = pulp.lpSum(X_SEP[c][1]*discountFactor['Bonus / ton [€/t]'][c] for
c in company)
# Objective function: TPC + TTC - TD -> min
alloc_prob += TPC_func + TTC_func - TD_funchttps://stackoverflow.com/questions/54217549
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