臺灣博碩士論文加值系統

存貨途程問題可視為車輛途程問題之延伸，決策者除了規劃原有的途程路線外，還需決定產品的配送時間與數量。為了節省存貨成本而增加配送次數，將造成運輸成本的提高；相對來說，為了降低配送成本而一次運送大量貨品則會使得存貨成本上升。透過精確的存貨途程規劃，可有效結合兩者，提升供應鏈系統整體之利潤，進而增進企業之競爭力。
隨著時代的進步，近年來人們對生鮮配送的需求與日俱增，除了超商、超市、量販店等通路商之生鮮商品種類有增無減，生鮮電商的崛起更將物流產業引領至新的格局。本研究將存貨途程問題結合生鮮產品之配送，再加上裝載器具之同時收送貨的作業特性，以最小總成本作為衡量指標建立數學模型，接著發展粒子群演算法作為本研究之求解演算法，最後以大小問題範例驗證所建構之數學模型及演算法。根據實驗結果，在啟用車輛為中小型冷藏車之情形下，生鮮商品較適合以短程多次的方式進行配送，且車容量大小對配送腐敗成本有著強烈的影響性。

Inventory Route Problems (IRPs) can be considered as an extending application of Vehicle Routing Problems (VRPs). In general, IRPs considers the factors of inventory management. Decision makers have to arrange not only the route but also when and how much to delivery. In order to save the inventory cost and increase the times of distribution would multiply the transportation cost. In the other hand, to decrease the transportation cost and delivery amount of goods in one time would cause the raising of the inventory cost. Consequently, through the accurate way to combine both the distribution and inventory planning could advance benefit of the whole supply chain system. So as to make the company become more competitively.
As time progresses, the need of fresh delivery has become much more than before. Including of convenience stores, supermarket and mall, there are more and more different kinds of fresh goods in these distributors and retailers. Even though the online stores add the fresh delivery service by the electronic commerce. A growing number of the enterprises enter into this area in recent years.
Our research combined both fresh delivery and IRPs. Moreover, to make sure the research more like the actual distribution situation, we considered the reusable characteristic of logistics boxes. Therefore we added the pickups and delivers condition in our research. Next, we constructed a model for our problem and let the minimum cost for measurable indicators. Then, we developed a Particle Swarm Optimization algorithm for solving our problem. Last but not least, we used different size of example to test our model and algorithm.
Due to the result of the research, in case of rental the medium or small refrigerated trucks, distribute in short way with multiple times would be suitable for fresh delivery. Furthermore, the capacity of the trucks has intense influence for the decayed delivery cost.

目錄
摘要 i
ABSTRACT ii
誌謝 iv
目錄 v
表目錄 viii
圖目錄 x
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 2
1.3 研究目的 3
1.4 研究範圍 4
1.5 研究架構 4
第二章 文獻探討 7
2.1 存貨途程問題 7
2.2 存貨途程求解辦法 10
2.2.1 傳統求解演算法 10
2.2.2 萬用啟發式演算法 15
2.2.3 田口實驗設計方法 25
2.3 同時收送貨的車輛途程問題 29
2.4 生鮮產品特性 31
2.5 考量易腐性產品配送之存貨途程問題相關數學模型探討 33
2.6 本研究相關文獻彙整 39
2.7 小結 41
第三章 研究方法 42
3.1 問題描述 42
3.2 基本限制與假設 43
3.3 數學模型建構 44
3.3.1 參數與變數定義 44
3.3.2 數學模型 46
3.4 數學模式驗證 48
3.4.1 例題說明 49
3.4.2 求解結果 50
3.5 建構求解演算法 52
3.5.1 配送期間規劃 52
3.5.2 初始途程建構 55
3.5.3 改善途程建構 58
第四章 範例測試與結果分析 62
4.1 參數設計 62
4.1.1 c1、c2與隨機函數參數之設定 62
4.1.2 慣性權重w之設定 63
4.1.3 粒子數目與迭代次數之分析 63
4.1.4 田口實驗設計結果 63
4.2 演算法品質測試 65
4.2.1 實驗例題說明 65
4.2.2 小規模例題求解 66
4.3 例題分析 69
4.3.1 送貨比例70%、收貨比例30%求解結果分析 73
4.3.2 送貨比例70%、收貨比例50%求解結果分析 73
4.4 敏感度分析 74
4.4.1 車容量的敏感度分析 74
4.4.2 零售商平均需求量的敏感度分析 77
4.5 小結 79
第五章 結論與未來研究方向 81
5.1 結論 81
5.2 未來研究方向 81
參考文獻 83

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