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研究生:張巧蓉
研究生(外文):Chiao-Jung Chang
論文名稱:多目標規劃與不確定性分析之結合--以地下水整治決策為例
指導教授:馬鴻文馬鴻文引用關係
指導教授(外文):Hwong-Wen Ma
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:環境工程學研究所
學門:工程學門
學類:環境工程學類
論文種類:學術論文
論文出版年:2001
畢業學年度:89
語文別:中文
論文頁數:97
中文關鍵詞:多目標規劃法隨機規劃法模糊規劃法不確定
外文關鍵詞:Mulitobjective programmingstochastic programmingfuzzy programminguncertainty
相關次數:
  • 被引用被引用:11
  • 點閱點閱:435
  • 評分評分:
  • 下載下載:113
  • 收藏至我的研究室書目清單書目收藏:3
早期環境工作者較注重於空氣、水污染等方面,而地下水污染在近幾年才逐漸被重視,但此污染整治卻是一件具高度複雜且不確定的環境問題,在面對資訊不足的情形下,如何整合出有用的資訊給決策者所參考是很重要的研究課題。
不確定下進行決策是本文所探討的重點,傳統的確定型規劃並無法呈現,故本研究嘗試以文獻中常見的隨機規劃及模糊規劃,處理不確定性對地下水整治決策的影響,並加入了整治成本及風險二個衝突的目標,使其更適合環境問題具多目標的特性,在滿足成本及風險最小化的情形下,選擇最適之整治方案,以提供決策者作為參考。
若資訊較充足,可得完整的機率密度函數,則以隨機規劃法處理較優,而在資訊較缺乏的情形下,模糊規劃法是一很好的替代工具。規劃結果顯示,不確定下之權重法結果在成本與風險權重比=0.5:0.5時,隨著百分比比較基準增加,結果由注氣法(b)改變至生物復育法(a)及自然復育法,而不確定下之妥協規劃法的結果是比較一致的;模糊規劃法的結果除Zimmermann法結合妥協規劃法無可行解外,其除皆要為注氣法(b),滿意度介於0.4608~0.6433之間。
Environmental Engineer paid much attention to air pollution and water pollution in early periods and only until recently did they focus on groundwater pollution. Goundwater pollution is a complex environmental problem with high uncertainty. Under the situation without enough information, it is important for decision makers to obtain guidance on the decision problems.
The main objective of this study is to develop a method of making decisions under uncertainty in a groundwater-contamination context. Since traditional deterministic programming can’t deal with uncertainty, this study uses stochastic programming and fuzzy programming to address the influence of uncertainty on groundwater remediation. Furthermore, multiobjective programming considering cost and health risk is incorporated with uncertainty analysis in this study to select optimal alternative with minimal health risk and remediation cost.
If there is enough information on probability density functions, stochastic programming should be the preferred approach; If no enough information is available, fuzzy programming should be used instead. The programming results of weighting method at Wcost:Wrisk=0.5:0.5 under uncertainty change from air sparging(b) to bioremediation(a) and then to natural attenuation with adding confidence levels. The results of compromise programming under uncertainty are similar, except that for compromise programming combined with Zimmermann method there is no feasible solution. The result derived from other combinations of fuzzy programming is air sparging(b), with membership degree between 0.4608 to 0.6433.
第一章 緒論
1-1研究緣起--------------------------------------------01
1-2研究目的與流程--------------------------------------02
第二章 文獻回顧
2-1多目標決策方法----------------------------------------05
2-1.1多目標決策方法的分類------------------------------07
2-1.2多目標決策方法的求解模式及方法--------------------08
2-2地下水中之不確定性------------------------------------16
2-2.1不確定下之數學規劃--------------------------------18
2-2.2隨機規劃法----------------------------------------18
2-2.3模糊規劃法----------------------------------------24
2-2.4不確定下之多目標規劃------------------------------34
2-3地下水整治技術----------------------------------------36
2-3.1抽出處理法----------------------------------------37
2-3.2自然復育法----------------------------------------38
2-3.3生物復育法----------------------------------------39
2-3.4注氣法--------------------------------------------41
2-3.5斗牆與阻門----------------------------------------42
2-4風險評估----------------------------------------------44
2-4.1危害性鑑定----------------------------------------44
2-4.2暴露評估------------------------------------------44
2-4.3劑量-反應評估-------------------------------------45
2-4.4風險特徵化----------------------------------------45
第三章 研究方法
3-1地下水傳流模式模擬------------------------------------48
3-1.1地下水流模擬--------------------------------------49
3-1.2污染物傳輸模擬------------------------------------54
3-1.3復育方案模擬--------------------------------------54
3-2優選模式----------------------------------------------58
3-2.1多目標規劃----------------------------------------63
3-2.2不確定下之多目標規劃------------------------------67
第四章 結果與討論
4-1地下水傳流模擬結果-----------------------------------71
4-2優選模擬結果-----------------------------------------74
4-2.1不確定下之多目標規劃-----------------------------74
第五章 結論與建議
5-1結論------------------------------------------------84
5-1.1多目標規劃之比較----------------------------------84
5-1.2隨機規劃與模糊規劃之比較--------------------------84
5-1.3整治方案之優選結果--------------------------------85
5-2建議------------------------------------------------86
第六章 參考文獻--------------------------------------88
附錄A-------------------------------------------A-1
附錄B-------------------------------------------B-1
List of Figures
Fig 1-1 Flow chart of research procedures-----------------------------04
Fig 2-1 Flowchart of Monte Carlo analysis ----------------------------23
Fig 2-2 Non-increasing ---------------------------------------------25
Fig 2-3 Non-decreasing --------------------------------------------25
Fig 2-4 Triangular membership function -----------------------------25
Fig 2-5 Trapezoid membership function -----------------------------25
Fig 2-6 Non-increasing---------------------------------------------26
Fig 2-7 Non-decreasing---------------------------------------------26
Fig 2-8 Pump and treat system--------------------------------------38
Fig 2-9 Diagram of biodegradation----------------------------------40
Fig 2-10 Air sparging system---------------------------------------42
Fig 2-11 Multiple parallel connection gate-------------------------43
Fig 2-12 Multiple series connection gate----------------------------43
Fig 2-13 Site of risk assessment -----------------------------------46
Fig 3-1 Research framework-----------------------------------------47
Fig 3-2 Possible effective porosity’s distribution----------------52
Fig 3-3 Advection and dispersion-----------------------------------55
Fig 3-4 Advection only---------------------------------------------55
Fig 3-5 Location of source and wells-------------------------------57
Fig 3-6 Flow chart for groundwater contamination transport and remediation simulation-----------------------------------58
Fig 3-7 Flow chart for optimization--------------------------------63
List of Tables
Table 2-1 Payoff table ---------------------------------------------13
Table 2-2 The payoff table of PIS------------------------------------28
Table 2-3 A taxonomy of FMODM methods------------------------------29
Table 2-4 Parameter programming table------------------------------31
Table 3-1 PCE’s sensitivity analysis------------------------------50
Table 3-2 TCE’s sensitivity analysis------------------------------51
Table 3-3 Hydrogeologic parameters---------------------------------53
Table 3-4 Properties of PCE、TCE-----------------------------------54
Table 3-5 The cost of treatment technology-------------------------59
Table 3-6 Remediation technology cost------------------------------62
Table 3-7 Payoff table---------------------------------------------64
Table 4-1 PCE concentration distribution---------------------------72
Table 4-2 TCE concentration distribution---------------------------72
Table 4-3 Risk distribution----------------------------------------73
Table 4-4 Payoff table (stochastic,50% percentile)----------------74
Table 4-5 Payoff table (stochastic,85% percentile)----------------75
Table 4-6 Payoff table (stochastic,95% percentile)----------------75
Table 4-7 The result of weighting method under stochastic programming
(50% percentile) -----------------------------------------76
Table 4-8 The result of compromise programming under stochastic programming (50% percentile)-----------------------------76
Table 4-9 The result of weighting method under stochastic programming
(85% percentile)-----------------------------------------77
Table 4-10 The result of compromise programming under stochastic programming(85% percentile)----------------------------77
Table 4-11 The result of weighting method under stochastic programming (95% percentile)-----------------------------------------78
Table 4-12 The result of compromise programming under stochastic programming (95% percentile)-----------------------------78
Table 4-13 Parametric programming table (weighting method,
Wcost:Wrisk=0.2:0.8)---------------------------------80
Table 4-14 Parametric programming table (compromise programming,
αcost:αrisk=0.2:0.8)-----------------------------------80
Table 4-15 Use weighting method as expected value---------------------82
Table 4-16 Use compromise programming as expected value-------------82
Table 4-17 Use weighting method as expected value---------------------83
Table 4-18 Use compromise programming as expected value---------------83
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