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研究生: 吳政遠
Wu, Cheng-Yuan
論文名稱: 以多目標演化演算法求解雙目標汙染車輛路由問題
Solving a Bi-objective Pollution Routing Problem Using Multi-objective Evolutionary Algorithms
指導教授: 蔣宗哲
Chiang, Tsung-Che
學位類別: 碩士
Master
系所名稱: 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2019
畢業學年度: 107
語文別: 中文
論文頁數: 50
中文關鍵詞: 多目標演化演算法車輛路由問題雙目標汙染車輛路由問題
英文關鍵詞: Evolutionary Algorithm, Vehicle Routing Problem, Pollution Routing Problem
DOI URL: http://doi.org/10.6345/THE.NTNU.DCSIE.006.2019.B02
論文種類: 學術論文
相關次數: 點閱:156下載:30
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  • 本論文使用多目標演化演算法NSGAIII求解雙目標汙染車輛路由問題 (Pollution Routing Problem),此問題為車輛路由問題 (Vehicle Routing Prolbem) 的延伸。雙目標汙染車輛路由問題中物流車有最大容量 (capacity) 限制;客戶與倉庫都有最早開始服務時間 (ready time) 與最晚服務時間 (due time),物流車必須在這段時間內抵達,此為時間限制。我們希望同時最小化總油耗量與最小化總花費時間,但速度在一定速度後越快變得越耗油,想要降低耗油會拉長花費時間,兩者無法同時下降。然而,我們可以求出非凌越解 (non-dominated solution),這些解在目標空間中形成柏拉圖前緣 (Pareto front),本論文的目標是求得接近此問題之真實解的柏拉圖前緣。
    我們使用最近鄰點法 (Nearest Neighborhood, NN) 初始化方式來使初始解具備一定品質。多目標路線建構來提前使解具有多目標特性與更具多樣性。探討多種速度對於汙染車輛路由問題的影響性。使用NEH與2-Opt搜尋法的來增強最小化總行駛距離來接近真實解之柏拉圖前緣。
    本論文提出的演算法在使解族群更具有多目標特性有較佳的效果。

    中文摘要 i 誌謝 ii 目錄 iii 附圖目錄 v 附表目錄 vi 第一章 緒論 1 1.1 研究動機 1 1.2 車輛路由問題 1 1.3 演化演算法 5 1.4 多目標最佳化問題 7 1.5 研究方法 8 1.6 論文架構 9 第二章 問題定義 10 第三章 文獻探討 16 3.1 綠能車輛路由 16 3.1.1 耗能因子 16 3.1.2 碳排放計算 17 3.1.3 求解GVRP之演算法 18 3.2 求解汙染車輛路由問題 19 3.2.1 精確演算法 19 3.2.2 常見的鄰域函式 20 3.2.3 適應性大規模鄰域搜尋法 (ALNS) 21 第四章 方法與實驗步驟 22 4.1 演算法架構 22 4.2 解的編碼 23 4.3 解的解碼(路線建構) 23 4.4 初始化族群 (initial population) 的產生 29 4.5 交配 29 4.6 區域搜尋法 30 4.6.1 NEH 30 4.6.2 2-Opt 32 4.7 速度優化演算法 33 第五章 實驗與結果 35 5.1 測試問題 35 5.2 效能指標 35 5.3 比較文獻 35 5.4 實驗與結果 36 5.4.1 隨機初始化與NN初始化之結果比較 36 5.4.2 多目標與單目標路線建構求解之比較 37 5.4.3 速度對於此問題的影響 40 5.4.4 區域搜尋有無之比較 43 5.4.5 與文獻之單目標比較 44 第六章 結論與未來研究方向 46 參考文獻 47

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