【正文】 I 摘 要 近年來，物流作為“第三方利潤的源泉”受到國內(nèi)各行業(yè)的極大重視并得到了較大的發(fā)展。 在高度發(fā)展的商業(yè)社會中，傳統(tǒng)的 VSP算法已無法滿足顧客需求對物流配送提出的要求，于是時間窗的概念應運而生。帶有時間窗的車輛優(yōu)化調(diào)度問題是比 VSP復雜程度更高的 NP 難題。 本文在研究 物流配送 車輛優(yōu)化調(diào)度問題的基礎上，對有時間窗的車輛優(yōu)化調(diào)度問題進行了分析。并對所采用的遺傳算法的基本理論做了論述。 對于有時間窗的非滿載 VSP 問題，將貨運量約束和軟時間窗約束轉化為目標約束，建立了非滿載VSP模型，設計了基于自然數(shù)編碼，使用最大 保留交叉、改進的反轉變異等技術的遺傳算法。經(jīng)實驗分析，取得了較好的結果。 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(shù)和變異操作的部分。 關鍵詞 ：物流配送 車輛優(yōu)化調(diào)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(diào)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(diào)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(diào)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(shù)向量編碼 ................................................................. 15 排列編碼 ....................................................................... 15 IV 適應度函數(shù) ............................................................................ 15 目標函數(shù)映射成適應度函數(shù) ............................................. 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(shù)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(shù)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(shù) .................................................................... 31 初始種群 ....................................................................... 31 遺傳算子 ....................................................................... 31 控制參數(shù)和終止條件 ....................................................... 32 算法實現(xiàn) ................................................................................ 34 實驗及結果分析 ...................................................................... 34 控制參數(shù)選定 ..............