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之研究

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張恭文(Kung-Wen Chung) 查詢紙本館藏

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土木工程學系

論文名稱

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之研究
(Ready Mixed Concrete Production and Truck Dispatching Planning When RMC Mixer Is Breakdown Unexpectedly under Stochastic Travel Times)

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摘要(中)

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。

摘要(英)

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.

關鍵字(中)

★ 預拌混凝土
★ 生產排班
★ 拌合車排程
★ 臨時事件
★ 隨機擾動
★ 時空網路
★ 含額外限制網路流動問題

關鍵字(英)

★ network flow problem with side constraints
★ time-space network
★ ready mixed concrete
★ production scheduling
★ truck dispatching
★ incident
★ stochastic disturbance

論文目次

摘要 I
ABSTRACT II
誌謝 III
目錄 IV
圖目錄 VII
表目錄 VIII
第一章緒論 1
1.1 研究背景與動機 1
1.2 研究目的與範圍 2
1.3 研究方法與程式架構 3
第二章文獻回顧 5
2.1現況分析 5
2.2預拌混凝土生產作業與拌合車調派問題 7
2.3工廠生產排程問題 9
2.4時窗限制之車輛派遣/排程問題 11
2.5時空網路之相關文獻 13
2.6隨機擾動之相關理論與文獻 15
2.6.1 隨機性問題相關理論 15
2.6.2 隨機擾動相關文獻 17
2.7 大型含額外限制之整數網路流動問題啟發式演算法 20
2.8 小結 23
第三章模式構建 25
3.1 問題描述 25
3.2 隨機性之即時拌合廠作業模式 25
3.2.1 模式條件設定 26
3.2.1.1 基本假設 26
3.2.1.2 給定資訊 28
3.2.2 時空網路 29
3.2.3 限制說明 36
3.2.4 非預期性懲罰成本( )設計 41
3.2.5 模式符號說明 44
3.2.6 數學定式 49
3.3 確定性之即時拌合廠作業模式 53
3.3.1 確定性模式之時空網路 53
3.3.2 符號說明 55
3.3.3 數學定式 55
3.4 模擬評估方法 57
3.5 小結 58
第四章模式求解 59
4.1 啟發解法架構 59
4.2 單一車輛定線法 62
4.3 目標值下限解 62
4.3 小結 63
第五章範例測試 64
5.1資料輸入 64
5.1.1澆置作業資料 64
5.1.2營運成本資料 65
5.2 模式發展 65
5.2.1 問題規模 65
5.2.2 模式輸入資料 67
5.3 電腦演算環境及設定 67
5.3.1 電腦演算環境 67
5.3.2 相關程式設定 68
5.3.3 模式輸出資料 68
5.4 測試結果與分析 69
5.4.1隨機狀況數目 70
5.4.2隨機性之即時拌合廠作業排程模式結果 71
5.4.3 模式比較分析 73
5.5 敏感度分析 75
5.5.1 拌合車規模敏感度分析 75
5.5.2 需求大小敏感度分析 77
5.5.3 隨機分配模式敏感度分析 79
5.5.3.1 平均數變動 79
5.5.3.2 標準差變動 81
5.5.4 違反冷縫限制懲罰成本( ) 82
5.5.5 達冷縫機率上限(100%)之時間感度分析 84
5.6情境分析 86
5.6.1拌合廠故障修復所需時間之情境分析 86
5.6.2開始規劃時間之情境分析 88
5.6.3問題規模大小之情境分析 90
5.6.4非預期性懲罰成本之冷縫機率分配型態情境分析 92
5.7小結 94
第六章結論與建議 95
6.1 結論 95
6.2 建議 96
6.3 貢獻 97
參考文獻 99
附錄 108
附錄一 CPLEX Callable Library Code 108
附錄二旅行時間分布圖 109
附錄三隨機狀況模擬數目測試結果 110
附錄四即時拌合廠作業班次 111
附錄五拌合車規模敏感度分析 113
附錄六隨機分配模式敏感度分析 114
附錄七違反冷縫限制懲罰成本敏感度分析結果 115
附錄八拌合廠及工地之營運時間 116

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指導教授

顏上堯(Shang-Yao Yan)

審核日期

2009-7-21

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