目前預拌混凝土的生產已進入自動化與電腦化的時期，但在混凝土生產作業安排與拌合車運送排程上，實務界仍以人工經驗的方式進行規劃。此方式缺乏系統最佳化分析，往往會造成資源的浪費，降低營運績效。雖然Yan and Lai (2007)與Yan et al. (2008)曾針對正常日與考量加班日等二種作業下之確定性預拌混凝土拌合廠生產排班與拌合車排程規劃問題，利用數學規劃方法，以最小營運成本目標，並考量相關營運限制下，分別構建一整合預拌混凝土生產排班和拌合車排程模式。然而，現實的營運上充滿了頗多的臨時或隨機事件以擾動原規劃的排程，例如在即時的營運中，當預拌混凝土廠遭遇臨時性的故障時，則預拌廠的生產作業受影響，連帶著拌合車的運送排程亦將受影響；又如在實際的營運中，各拌合廠至各工地間之旅行時間常為隨機值(可能成某種分佈)，並非為一固定值，其值將影響拌合車的運送排程規劃與績效。因此本研究以系統最佳化的觀點，針對隨機旅行時間下拌合廠臨時性故障之混凝土生產與拌合車派遣規劃問題發展適合之模式及求解演算法，以提供決策者輔助工具，有效地規劃拌合廠的生產排班與拌合車的運送排程。 本研究利用時空網路流動技巧以定式拌合車在時空中的流動狀況及預拌廠在時間中的生產情況，並根據問題特性加入適當的額外限制，以滿足實務的營運條件，並據以構建模式。本模式可定式為含額外限制之整數網路流動問題，屬NP-hard問題，在面對實務大型的問題時，難以在有限的時間內求得最佳解。因此，為有效地求解實務大型問題，本研究利用問題分解策略，並配合使用數學規劃套裝軟體CPLEX，發展一有效的求解演算法。最後，為評估本模式與演算法之實際求解績效，本研究以台灣一拌合廠之實際營運資料為範例進行測試與分析，結果甚佳，顯示本研究所發展之模式與求解演算法可為實務業者之參考，以有效地處理隨機旅行時間下混凝土生產與拌合車排程擾動問題。 The production of ready mixed concrete (RMC) has been automatic and computerized, but the RMC production scheduling and truck dispatching are still manually determined with staff experience. Consequently, the resulting solution, though feasible, could possibly be inferior. Yan and Lai (2007) and Yan et al. (2008) have respectively developed a deterministic model that combines RMC production scheduling and truck dispatching in the same framework, for general and overtime conditions. However, in actual operations many stochastic incidents may occur to disturb the original plan. For example, if an RMC plant is broken down, then both the RMC production scheduling and truck dispatching would be affected. Moreover, the travel time between an RMC plant and a construction site is usually stochastic (particularly with a certain distribution) in practice, which could affect the RMC production scheduling and truck dispatching. Therefore, in this research we focus on the RMC production and truck schedule adjustment problem under stochastic travel time when an RMC mixer is broken down unexpectedly to develop a suitable model from the system optimization perspective. The model is expected to be useful planning tool for carriers to decide on their optimal RMC production scheduling and truck dispatching in their operations. We employ time-space network flow techniques to formulate the RMC truck flows and the RMC production in the dimension of time and space, coupled with suitable side constaints comply real operating requirements, to develop the model. The model is formulated as an integer network flow problem with side constraints, which is characterized as NP-hard and is difficult be be optimally solved in a reasonable time for large-scale problems. In order to efficiently solve large-scale problems occurring in real world, we develop a solution algorithm. To evaluate the model and solution algorithms, we perform a case s`tudy using real operating data from a Taiwan RMC firm. The test results show that the model and the solution algorithm are good and could be useful references for carriers to handle RMC productin and truck schedule perturbations under stochastic travel times.
