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用遺傳算法解決車輛優(yōu)化調度問題—免費畢業(yè)設計論文-wenkub

2022-12-12 15:53:18 本頁面
 

【正文】 業(yè)的重點是如何將車輛有效的使用并決定其最經濟的行駛路線圖,使商品能在最短的時間內送到顧客的手中。物流中心的功能就在于對商品的倉儲與運輸進行有效的統(tǒng)籌規(guī)劃以降低配送成本?!迸渌褪窃诩?貨、配貨基礎上,按用戶要求,包括種類、品種搭配、數量、時間等方面的要求所進行的運送,是“配”和“送”的有機結合形式,其主要功能是輸送。 據中國物流信息中心統(tǒng)計測算, 2021 年,全國社會物流總額達 萬億元,同比增長 %(按現價計算 ),增幅比上年同期提高 個百分點。 目前國內采用遺傳算法解決物流配送的車輛優(yōu)化調度問題的研究還處在起步階段。 由于此問題為小組成員共同研究,本文重點論述了本人完成的關于適應度函數和變異操作的部分。 本文在研究 物流配送 車輛優(yōu)化調度問題的基礎上,對有時間窗的車輛優(yōu)化調度問題進行了分析。 I 摘 要 近年來,物流作為“第三方利潤的源泉”受到國內各行業(yè)的極大重視并得到了較大的發(fā)展。并對所采用的遺傳算法的基本理論做了論述。 關鍵詞 :物流配送 車輛優(yōu)化調度 遺傳算法 時間窗 II Abstract Recent years, logistics, taken as third profit resource”, has been developing rapidly. In the developed mercial society, traditional VSP algorithm have been unable to meet the requirement that Quick Response to customer demand had brought forth, then the conception of Time Window has e into being. The vehiclescheduling problem with time window is also a NPhard problem being more plicated than VSP. This text has been researched to the vehiclescheduling problem with time window on the basis of researched to logistic vehicle scheduling problem. And it has explained the basic theory of geic algorithm. On the VSP with time window, while the restraints of capacity and time windows are changed into object restraints, a mathematic model is established. We use technique such as maximum preserved crossover and design geic algorithm on nature number, which can deal with soft time windows through experimental analysis, have made better result. Because this problem was studied together for group members, this text has expounded the part about fitness function and mutation operator that I finished. Key words: logistic distribution vehicle scheduling problem geic algorithm time windows III 目 錄 摘 要 .....................................................................................................I Abstract ................................................................................................ II 目 錄 .................................................................................................. III 引 言 .................................................................................................... 1 第 1 章 概 述 ...................................................................................... 2 研究背景 .................................................................................. 2 物流配送車輛優(yōu)化調度的研究動態(tài)和水平 ................................... 4 問題的提出 ...................................................................... 4 分類 ................................................................................ 4 基本問題與基本方法 ......................................................... 5 算法 ................................................................................ 5 貨運車輛優(yōu)化調度問題的分類 ........................................... 6 研究的意義 .............................................................................. 7 研究的范圍 .............................................................................. 7 第 2 章 有時間窗的車輛優(yōu)化調度問題 (VSPTW) ...................................... 9 時間窗的定義 ........................................................................... 9 VSPTW 問題的結構 ................................................................... 11 第 3 章 遺傳算法基本理論 .................................................................. 11 遺傳算法的基本原理 ............................................................... 11 遺傳算法的特點 ............................................................. 12 遺傳算法的基本步驟和處理流程 ...................................... 12 遺傳算法的應用 ............................................................. 13 編碼 ...................................................................................... 14 二進制編碼 .................................................................... 14 Gray 編碼 ...................................................................... 15 實數向量編碼 ................................................................. 15 排列編碼 ....................................................................... 15 IV 適應度函數 ............................................................................ 15 目標函數映射成適應度函數 ............................................. 16 適應度定標 .................................................................... 16 遺傳算法的基因操作 ............................................................... 17 選擇算子 ....................................................................... 17 交叉算子 ....................................................................... 18 變異算子 ....................................................................... 21 遺傳算法控制參數設定 ............................................................ 24 第 4 章 遺傳算法求解有時間窗非滿載 VSP ........................................... 25 問題描述 ................................................................................ 25 數學模型 ................................................................................ 25 一般 VSP 模型 ................................................................. 25 有時間窗 VSP 模型 .......................................................... 27 算法設計 ................................................................................ 27 算法流程圖 .................................................................... 27 染色體結構 .................................................................... 27 約束處理 ....................................................................... 30 適應度函數 .................................................................... 31 初始種群 ....................................................................... 31 遺傳算子 ....................................................................... 31 控制參數和終止條件 ....................................................... 32 算法實現 ................................................................................ 34 實驗及結果分
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