Solving Container Loading Problems By Co-operative Co-evolutionary Genetic Algorithm 賴志昌、吳泰熙



Solving Container Loading Problems By Co-operative Co-evolutionary Genetic Algorithm 賴志昌、吳泰熙



Container loading problems are frequently encountered in indus-tries such as manufacturing, food and logistics. A good utilization of containers can always result in cost savings. Container loading prob-lems are of the NP-Complete type, and they are solved to be efficient by genetic algorithm. This thesis proposed a new co-operative co-evolutionary genetic algorithm (C.C.G.A.) for solving container loading problem. The pro-posed heuristic rule is used to partition the entire loading sequence into a number of shorter sequences. Each partitioned sequence is then rep-resented by a species member in the CCGA search. And it is used by ” bottom-back-left ” packing approach in compliance with simulation results.

Keywords : container, loading, genetic algorithms, co-operative co-evolutionary genetic algorithm.

Table of Contents

目 錄 封面內頁 簽名頁 授權書 iii 中文摘要 iv ABSTRACT v 誌謝 vi 目錄 vii 圖目錄 ix 表目錄 x 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 研究限制 2 1.4 研究方法與架構 3 第二章 文獻探討 5 2.1 長方體物件與長方體容器 5 2.2 演算法 8 2.3 「下後左角」優先之啟發式堆疊 9 第三章 長方體物件堆疊問題求解 12 3.1 問題定義 12 3.2 遺傳基因演算法 13 3.2.1 協 力進化遺傳演算法 14 3.2.2 編碼 16 3.2.3 染色體數與產生母體數 16 3.2.4 選擇機制 18 3.2.5 交配 19 3.2.6 突變 20 3.2.7 終止 條件 21 3.2.8 遺傳基因演算流程 21 3.3 協力進化遺傳演算法之建立於長方體物件堆疊問題………… 22 第四章 演算結果與 分析 25 4.1 文獻例題簡介 25 4.2 參數設定與實驗數據 26 4.3 執行結果與分析 31 第五章 結論與建議 34 5.1 研究總結 34 5.2 建議 35 參考文獻 36 圖目錄 圖1.1 研究流程圖 4 圖2.1 物件擺放1 10 圖2.2 物件擺放2 11 圖3.1 編碼順序 16 圖3.2 物件子族群 分類 17 圖3.3 物件順序 17 圖3.4 基因合併組合 18 圖3.5 協力進化遺傳演算法 24 圖4.1 CCGA與文獻比較 32 表目錄 表2.1 長 方體物件堆疊問題文獻整理 7 表2.2 演算法文獻整理 8 表3.1 各條件允許的堆疊情形 13 表4.1 測試例題一 27 表4.2 測試例題 二 28 表4.3 測試例題三 29 表4.4 測試例題四 30 表4.5 CCGA與文獻比較結果 33 表4.6 CCGA執行結果 33


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