PuLP: Objective 函数:连接多个 lpSum

PuLP: Objective Function: Concatenate multiple lpSum

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 objective 函数。然而,我试图以优雅的方式合并这些表达式导致了不希望的结果。

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)]

输出符合预期。然而,这既不是一个好的代码,也不能分配给 objective 函数。有没有聪明的实施方式?

谢谢!

在没有看到错误的情况下,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_func