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MATLAB智能算法30个案例分析（第2版）

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Jingdong book

MATLAB智能算法30个案例分析（第2版）

Name: MATLAB智能算法30个案例分析（第2版）
Brand: Jingdong book
SKU: 3118012491
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《MATLAB智能算法30个案例分析（第2版）》是作者多年从事算法研究的经验总结.书中所有案例均应国内各大MATLAB技术论坛网友的切身需求而精心设计,其中不少案例所涉及的内容和求解方法在国内现已出版的MATLAB书籍中鲜有介绍.

《MATLAB智能算法30个案例分析（第2版）》采用案例形式,以智能算法为主线,讲解了遗传算法、免疫算法、退火算法、粒子群算法、鱼群算法、蚁群算法和神经网络算法等最常用的智能算法的MATLAB实现.本书共给出３０个案例,每个案例都是一个使用智能算法解决问题的具体实例,所有案例均由理论讲解、案例背景、MATLAB程序实现和扩展阅读四个部分组成,并配有完整的程序源码和讲解视频,使读者在掌握算法的同时,也可以学习到作者们多年积累的编程经验与技巧,从而快速提高使用算法求解实际问题的能力.

《MATLAB智能算法30个案例分析（第2版）》可作为本科毕业设计、研究生项目设计、博士低年级课题设计参考书籍,同时对广大科研人员也有很高的参考价值.

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第1章谢菲尔德大学的MATLAB遗传算法工具箱 1
1.1理论基础 1
1.1.1遗传算法概述 1
1.1.2谢菲尔德遗传算法工具箱 1
1.2案例背景 3
1.2.1问题描述 3
1.2.2解题思路及步骤 3
1.3MATLAB程序实现 3
1.3.1工具箱结构 3
1.3.2遗传算法常用函数 4
1.3.3遗传算法工具箱应用举例 12
1.4延伸阅读 16
参考文献 16
第2章基于遗传算法和非线性规划的函数寻优算法 17
2.1理论基础 17
2.1.1非线性规划 17
2.1.2非线性规划函数 17
2.1.3遗传算法基本思想 18
2.1.4算法结合思想 18
2.2案例背景 18
2.2.1问题描述 18
2.2.2算法流程 18
2.2.3遗传算法实现 19
2.3MATLAB程序实现 20
2.3.1适应度函数 20
2.3.2选择操作 20
2.3.3交叉操作 21
2.3.4变异操作 22
2.3.5算法主函数 23
2.3.6非线性寻优 24
2.3.7结果分析 24
2.4延伸阅读 25
2.4.1其他函数的优化 25
2.4.2其他优化算法 26
参考文献 26
第3章基于遗传算法的BP神经网络优化算法 27
3.1理论基础 27
3.1.1BP神经网络概述 27
3.1.2遗传算法的基本要素 27
3.2案例背景 27
3.2.1问题描述 27
3.2.2解题思路及步骤 29
3.3MATLAB程序实现 31
3.3.1神经网络算法 31
3.3.2遗传算法主函数 32
3.3.3比较使用遗传算法前后的差别 34
3.3.4结果分析 35
3.4延伸阅读 37
参考文献 37
第4章基于遗传算法的TSP算法 38
4.1理论基础 38
4.2案例背景 38
4.2.1问题描述 38
4.2.2解决思路及步骤 39
4.3MATLAB程序实现 40
4.3.1种群初始化 40
4.3.2适应度函数 40
4.3.3选择操作 41
4.3.4交叉操作 41
4.3.5变异操作 43
4.3.6进化逆转操作 43
4.3.7画路线轨迹图 43
4.3.8遗传算法主函数 44
4.3.9结果分析 47
4.4延伸阅读 48
4.4.1应用扩展 48
4.4.2遗传算法的改进 49
4.4.3算法的局限性 49
参考文献 49
第5章基于遗传算法的LQR 控制器优化设计 50
5.1理论基础 50
5.1.1LQR控制 50
5.1.2基于遗传算法设计LQR控制器 50
5.2案例背景 51
5.2.1问题描述 51
5.2.2解题思路及步骤 52
5.3MATLAB程序实现 53
5.3.1模型实现 53
5.3.2遗传算法实现 54
5.3.3结果分析 56
参考文献 56
第6章遗传算法工具箱详解及应用 57
6.1理论基础 57
6.1.1遗传算法的一些基本概念 57
6.1.2遗传算法与直接搜索工具箱 58
6.2案例背景 58
6.2.1问题描述 58
6.2.2解题思路及步骤 59
6.3MATLAB程序实现 59
6.3.1GADST各函数详解 59
6.3.2GADST的使用简介 63
6.3.3使用GADST求解遗传算法相关问题 66
6.4延伸阅读 68
参考文献 68
第7章多种群遗传算法的函数优化算法 69
7.1理论基础 69
7.1.1遗传算法早熟问题 69
7.1.2多种群遗传算法概述 69
7.2案例背景 70
7.2.1问题描述 70
7.2.2解题思路及步骤 71
7.3MATLAB程序实现 71
7.3.1移民算子 72
7.3.2人工选择算子 72
7.3.3目标函数 73
7.3.4标准遗传算法主函数 73
7.3.5多种群遗传算法主函数 74
7.3.6结果分析 75
7.4延伸阅读 76
参考文献 77
第8章基于量子遗传算法的函数寻优算法 78
8.1理论基础 78
8.1.1量子遗传算法概述 78
8.1.2量子比特编码 78
8.1.3量子门更新 79
8.2案例背景 79
8.2.1问题描述 79
8.2.2解题思路及步骤 80
8.3MATLAB程序实现 82
8.3.1种群初始化 82
8.3.2测量函数 82
8.3.3量子旋转门函数 83
8.3.4适应度函数 84
8.3.5量子遗传算法主函数 85
8.3.6结果分析 87
8.4延伸阅读 87
参考文献 88
第9章基于遗传算法的多目标优化算法 89
9.1理论基础 89
9.1.1多目标优化及Pareto最优解 89
9.1.2函数gamultiobj 89
9.1.3函数gamultiobj中的一些基本概念 90
9.2案例背景 90
9.2.1问题描述 90
9.2.2解题思路及步骤 90
9.3MATLAB程序实现 91
9.3.1gamultiobj组织结构 91
9.3.2函数stepgamultiobj分析 92
9.3.3使用函数gamultiobj求解多目标优化问题 99
9.3.4结果分析 100
参考文献 101
第10章基于粒子群算法的多目标搜索算法 102
10.1理论基础 102
10.2案例背景 102
10.2.1问题描述 102
10.2.2算法流程 103
10.2.3适应度计算 103
10.2.4筛选非劣解集 103
10.2.5粒子速度和位置更新 103
10.2.6粒子最优 104
10.3MATLAB程序实现 104
10.3.1种群初始化 104
10.3.2种群更新 104
10.3.3更新个体最优粒子 105
10.3.4非劣解筛选 105
10.3.5仿真结果 106
10.4延伸阅读 107
参考文献 107
第11章基于多层编码遗传算法的车间调度算法 108
11.1理论基础 108
11.2案例背景 108
11.2.1问题描述 108
11.2.2模型建立 108
11.2.3算法实现 109
11.3MATLAB程序实现 110
11.3.1主函数 110
11.3.2适应度值计算 111
11.3.3交叉函数 113
11.3.4变异函数 113
11.3.5仿真结果 114
11.4案例扩展 115
11.4.1模糊目标 115
11.4.2代码分析 116
11.4.3仿真结果 117
参考文献 117
第12章免疫优化算法在物流配送中心选址中的应用 118
12.1理论基础 118
12.1.1物流中心选址问题 118
12.1.2免疫算法的基本思想 118
12.2案例背景 119
12.2.1问题描述 119
12.2.2解题思路及步骤 120
12.3MATLAB程序实现 122
12.3.1免疫算法主函数 122
12.3.2多样性评价 123
12.3.3免疫操作 124
12.3.4仿真实验 127
12.4案例扩展 128
参考文献 129

Introduction

时光荏苒，如白驹过隙，转眼间，？MATLAB智能算法30个案例分析？已经陪伴各位读者走过了四个年头.在这期间，该书得到了广大读者的全面支持与包容，让我们备受鼓舞.
但自R2010a和R2010b以后，MATLAB对优化工具箱和神经网络工具箱进行了较大幅度的更新，与？MATLAB智能算法30个案例分析？一书相关的更新有：
① 自R2010a以后，遗传算法与直接搜索工具箱（GeneticAlgorithmandDirectSearchToolGbox，GADST）被集成到GlobalOptimizationToolbox中，其路径为MATLAB 安装目录\toolbox\globaloptim.
② 自R2010b以后，神经网络工具箱（NeuralNetworkToolbox）对BP神经网络、竞争神经网络、自组织特征映射神经网络等模型的创建、训练和预测函数进行了升级.为了方便读者学，？MATLAB智能算法30个案例分析（第2版）？对上一版的内容进行了以下修订：
① MATLAB编程环境从R2009a版本升级到了R2014a版本.在新版本中，读者可以更加简单、方便地完成程序的实现，从而可以将更多的精力集中于算法的设计方面.
② 增加了配套光盘，其中包括各个章节的程序源码和讲解视频.程序源码部分兼容了R2009a和R2014a两个版本，读者可以根据自身情况灵活选择.配套视频中除了包括对各个案例的详细讲解外，还包含了作者多年积累的编程经验与技巧，相信读者可以从中获益良多.
③ 丰富了读者与作者的交流途径与渠道.除了在MATLAB技术论坛书的交流版块参与交流，读者还可以加入该书的QQ 读者交流群），与作者以及其他读者一起交流学习，作者会不定期地组织一些集体答疑与讨论活动.
本次修订工作由郁磊统筹完成，其中，郁磊修订的章节包括：3、5、6、9、14、21、22和25~30；史峰修订的章节包括：2、10~13、15~17、23~24；王辉修订的章节包括：1、3、4、7~8、18~20.除了上述修订内容外，？MATLAB智能算法30个案例分析（第2版）？还勘误了上一版中存在的一些错误.在此过程中，得到了许多读者的帮助，如MATLAB技术论坛上的denyu、kirchhof、qiuzhichang和prado5等，在此不一一列举，衷心感谢他们！
对作者而言，过去的四年变化太多，有的作者出国深造，有的作者进入职场，有的作者娶妻生子，在此诚挚地感谢每一位作者的家人和朋友在背后的默默付出与支持，这是本书得以完成的最大动力与保障.然而不变的是，作者们依旧保持着那份初心与激情，随时准备着与每一位读者交流与探索，携手进步与成长！
作者
2015年7月2日于苏州

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