臺灣博碩士論文加值系統

　　近年來民眾對於資源回收意識已逐漸提高，而回收點的設立是經常採取的方式，過去的文獻在這方面也已有一些研究，但在設施區位問題方面，僅針對中位問題（P-median）的模式作探討，鮮少以pq-median的區位模式做研究，本研究為了更符合實際情況，將以pq-median的區位模式，提出一非線性混整數規劃的數學模型，求解在回收點與回收中心有容量限制的條件下，回收點及回收中心最佳的數量及位址、各個回收點之收集期間與顧客、回收點及回收中心三者之間的指派關係，使逆向物流系統總成本最小化。
對於此逆向物流的區位指派問題，本研究建立一啟發式演算法進行求解，再與基因演算法做求解品質與求解時間的比較；在總節點數20、40與60的三個範例題目下測試，結果證實與基因演算法相較之下，啟發式演算法的求解品質與求解時間皆優於基因演算法。在敏感度分析方面，針對收集期間之最大值 之影響做進一步的說明，以供決策者做參考。

Recycling conscious has been rising in recent years, and action taken frequently is setting a collection point, and it has been shown in some past research. In facility location-allocation that only addresses on p-median location model but not is pq-median. Therefore, for conforming to practical situation in this research, in limited capacity of collection points and centralized return centers, bringing up nonlinear mixed-integer programming model by pq-median location model reduces total cost in reverse logistics because of the connection among the best quantities and places of collection points and centralized return center, holding period for each collection point, and customers, collection points and centralized return center.
Figuring out location allocation problem in reverse logistics by building heuristic algorithm compared with genetic algorithm for solving quality and solving time; this report proves that heuristic algorithm is better than genetic algorithm in three different illustrations. In sensitivity analysis, further demonstration to the maximum of holding period is for decision maker reference.

目錄∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙i

表目錄∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙iv

圖目錄∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙vi

一、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∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙3
1.4研究架構與流程∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙3
二、文獻探討∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙6
2.1區位問題∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙6
2.2逆向物流定義及資源回收制度∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙9
2.3逆向物流區位指派問題相關文獻∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙11
2.4基因演算法∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙15
2.4.1編碼與解碼∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙15
2.4.2初始族群∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙15
2.4.3適合度函數值∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙16
2.4.4複製∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙16
2.4.5交配∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙17
2.4.6突變∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙18
2.4.7取代∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙18
2.4.8結束條件∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙18
2.5小結∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙20
三、模式與演算法建構∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙22
3.1基本問題描述∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙22
3.2模式建構∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙25
3.2.1基本假設與限制∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙25
3.2.2本研究求解問題之模式∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙25
3.3模式求解∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙29
3.3.1簡例一之描述∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙29
3.3.2簡例一之結果分析－LINGO 10.0 ∙∙∙∙∙∙∙30
3.4啟發式演算法之建構∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙32
3.4.1編碼∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙32
3.4.2初始母體之產生∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙34
3.4.3適合度函數值計算∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙34
3.4.4半群體重生法∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙35
3.4.5收斂條件∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙37
3.4.6移步－回收點之收集期間∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙37
3.4.7終止條件∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙39
3.4.8啟發式演算法求解步驟及流程圖∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙39
3.4.9啟發式演算法的驗證∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙43
3.4.9.1簡例二說明∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙43
3.4.9.2簡例二之結果分析－LINGO 10.0 ∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙45
3.4.9.3簡例二之演算過程與結果分析－啟發式演算法∙∙∙∙∙∙∙∙∙∙∙∙∙ 46
3.5基因演算法之建構∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙52
3.5.1染色體的編碼∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙52
3.5.2適合度函數值∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙53
3.5.3複製∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙53
3.5.4交配∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙54
3.5.5突變∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙55
3.5.6菁英政策∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙56
3.5.7終止條件∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙56
3.5.8基因演算法求解步驟及流程∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙56
四、參數設定與例題測試∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙59
4.1測試題庫∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙59
4.2參數設定∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙61
4.2.1啟發式演算法－參數設定∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙61
4.2.1.1初始母體數、收斂條件、停止條件∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙61
4.2.2基因演算法－參數設定∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙64
4.2.1.1母體數、交配率、突變率、世代
∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙64
4.3數值範例求解結果∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙68
4.4啟發式演算法演化機制分析∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙71
4.4.1指派法則之績效分析∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙71
4.4.2半群體重生法與移步之績效分析∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙73
4.5參數敏感度分析∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙76
五、結論與建議∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙84
5.1結論∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙84
5.2未來研究方向∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙85
參考文獻∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙86
附錄一：LINGO範例題目（一）測試∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙88
附錄二：LINGO範例題目（二）測試∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙92
附錄三：測試範例之相關數據∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙96
附錄四：測試範例結果之示意圖∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙111

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