臺灣博碩士論文加值系統

隨著全球化的市場越趨競爭，供應鏈的重要程度也越顯重要，企業為快速滿足客戶需求縮短產品生產週期使得產品運輸時間日趨嚴苛。不同的環境、地形及車種皆會影響到運輸可靠度，為了能將原料、產品正確且完整的送達客戶手中，運輸作業的規劃顯得格外重要。
本研究探討多目標供應鏈網路運輸問題，進一步將規模經濟、數量折扣等概念導入最佳化決策模式中，改良現有演算法容易陷入區域最佳解的狀況且使能夠更廣泛應用於各式供應鏈運輸網路問題。ISPGA演算法引用貪婪的概念再以最小成本法進行染色體編碼以求得較佳初始解，加入優化機制提高演算的效率以有效逼近全域最佳解，並利用田口實驗設計方法推算出最佳參數，最後將ISPGA演算法導入案例與其他三個多目標演算法MOPSO、SMPSO、NSGAII進行分析比較，結果顯示ISPGA演算法具有較佳的求解效率。

The market has become more competitive with the globalization, so the supply chain is more important than before. The enterprises in order to satisfy customer''s demand quickly and shorten the product’s cycle time to make the product’s transportation time increasingly stringent. Different environments, terrain and types of vehicles will affect the transportation reliability. In order to correct and complete the delivery to customers, the transportation planning is particularly important. The study is to discuss the multi-objective supply chain network transportation problems. This study consider the concept of economies of scale, volume discounts, optimize decision-making model. In order to avoid falling into local optimal solution, we modify our algorithm and make it more and more useful. ISPGA algorithm refers to the general idea of greedy algorithm, and least-cost method. This study uses ISPGA algorithm to encode chromosome and get superior optimization solution than before. Additionally, this study adds the optimization operation and Taguchi method to improve the calculation efficiency approaching the global optimized solution and calculate the optimal parameters. Finally, we compare three algorithm with MOPSO、SMPSO and NSGAII, the result shows that ISPGA algorithm has a superior solution efficiency.

摘要 i
Abstract ii
誌謝 iii
目錄 iv
表目錄 v
圖目錄 vi
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 論文架構 2
第二章 文獻探討 4
2.1供應鏈網路定義 4
2.2供應鏈網路相關文獻 5
2.3 運輸問題 9
2.4數量折扣 10
2.5規模經濟 13
2.6多目標最佳化 14
第三章 研究方法 17
3.1 問題描述與定義 17
3.2 研究架構 18
3.3 數學模式 20
第四章ISPGA演算法程序 24
第五章 案例導入與結果分析 29
5.1績效指標 29
5.2參數設定 30
5.3結果比較 32
5.4 案例導入結果 37
第六章 結論 42
參考文獻 43

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