PuLP:目标函数:连接多个 lpSum

我试图将几个lpSum表达式连接到一个长表达式,这将是我的目标函数。然而,我以优雅的方式合并这些表达式的尝试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


对我的代码更具体:



    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)]

输出做它应该做的。然而,这既不是一个很好的代码,也不能分配给目标函数。有没有聪明的实施方式?


catspeake
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1回答

杨__羊羊

没有看到错误,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 -> minalloc_prob += TPC_func  + TTC_func - TD_func
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