我試圖將幾個lpSum表達式連接到一個長表達式，這將是我的目標函數。然而，我以優雅的方式合并這些表達式的嘗試導致了不希望的結果。我想要這樣的東西：a = pulp.lpSum(...)b = pulp.lpSum(...)c = pulp.lpSum(...)prob += a + b - c對我的代碼更具體：    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我已經嘗試過不同的嵌套方法，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)]輸出做它應該做的。然而，這既不是一個很好的代碼，也不能分配給目標函數。有沒有聰明的實施方式？