【TSP】基于matlab GUI改进的遗传算法求解旅行商问题【含Matlab源码 926期】

一、TSP简介

旅行商问题，即TSP问题（Traveling Salesman Problem）又译为旅行推销员问题、货郎担问题，是数学领域中著名问题之一。假设有一个旅行商人要拜访n个城市，他必须选择所要走的路径，路径的限制是每个城市只能拜访一次，而且最后要回到原来出发的城市。路径的选择目标是要求得的路径路程为所有路径之中的最小值。
TSP的数学模型

二、遗传算法简介

1 引言

2 遗传算法理论
2.1 遗传算法的生物学基础

2.2 遗传算法的理论基础

2.3 遗传算法的基本概念

2.4 标准的遗传算法

2.5 遗传算法的特点

2.6 遗传算法的改进方向

3 遗传算法流程

4 关键参数说明

三、部分源代码

function varargout = tsp_ga_gui(varargin)
% TSP_GA_GUI MATLAB code for tsp_ga_gui.fig
%      TSP_GA_GUI, by itself, creates a new TSP_GA_GUI or raises the existing
%      singleton*.
%
%      H = TSP_GA_GUI returns the handle to a new TSP_GA_GUI or the handle to
%      the existing singleton*.
%
%      TSP_GA_GUI('CALLBACK',hObject,eventData,handles,...) calls the local
%      function named CALLBACK in TSP_GA_GUI.M with the given input arguments.
%
%      TSP_GA_GUI('Property','Value',...) creates a new TSP_GA_GUI or raises the
%      existing singleton*.  Starting from the left, property value pairs are
%      applied to the GUI before tsp_ga_gui_OpeningFcn gets called.  An
%      unrecognized property name or invalid value makes property application
%      stop.  All inputs are passed to tsp_ga_gui_OpeningFcn via varargin.
%
%      *See GUI Options on GUIDE's Tools menu.  Choose "GUI allows only one
%      instance to run (singleton)".
%
% See also: GUIDE, GUIDATA, GUIHANDLES% Edit the above text to modify the response to help tsp_ga_gui% Last Modified by GUIDE v2.5 25-Feb-2021 15:15:58% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...'gui_Singleton',  gui_Singleton, ...'gui_OpeningFcn', @tsp_ga_gui_OpeningFcn, ...'gui_OutputFcn',  @tsp_ga_gui_OutputFcn, ...'gui_LayoutFcn',  [] , ...'gui_Callback',   []);
if nargin && ischar(varargin{1})gui_State.gui_Callback = str2func(varargin{1});
endif nargout[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
elsegui_mainfcn(gui_State, varargin{:});
end
% End initialization code - DO NOT EDIT% --- Executes just before tsp_ga_gui is made visible.
function tsp_ga_gui_OpeningFcn(hObject, eventdata, handles, varargin)
global hnds
global r nn dsm asz G
global startf% Choose default command line output for tsp_ga_gui
handles.output = hObject;% Update handles structure
guidata(hObject, handles);% UIWAIT makes tsp_ga_gui wait for user response (see UIRESUME)
% uiwait(handles.figure1);hnds=handles;startf=false; % start flagasz=10; % area size   asx x asz
nn=str2num(get(handles.nn,'string')); % number of cities
ps=str2num(get(handles.ps,'string')); % population sizer=asz*rand(2,nn); % randomly distribute cities
% r(1,:) -x coordinaties of cities
% r(2,:) -y coordinaties of citiesdsm=zeros(nn,nn); % matrix of distancies
for n1=1:nn-1r1=r(:,n1);for n2=n1+1:nnr2=r(:,n2);dr=r1-r2;dr2=dr'*dr;drl=sqrt(dr2);dsm(n1,n2)=drl;dsm(n2,n1)=drl;end
end% start from random closed pathes:
G=zeros(ps,nn); % genes, G(i,:) - gene of i-path, G(i,:) is row-vector with cities number in the path
for psc=1:psG(psc,:)=randperm(nn);
endupdate_plots;% --- Outputs from this function are returned to the command line.
function varargout = tsp_ga_gui_OutputFcn(hObject, eventdata, handles)
% varargout  cell array for returning output args (see VARARGOUT);
% hObject    handle to figure
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)% Get default command line output from handles structure
varargout{1} = handles.output;% --- Executes on button press in randomize.
function randomize_Callback(hObject, eventdata, handles)
global r nn dsm asznn=str2num(get(handles.nn,'string')); % number of citiesr=asz*rand(2,nn); % randomly distribute cities
% r(1,:) -x coordinaties of cities
% r(2,:) -y coordinaties of citiesdsm=zeros(nn,nn); % matrix of distancies
for n1=1:nn-1r1=r(:,n1);for n2=n1+1:nnr2=r(:,n2);dr=r1-r2;dr2=dr'*dr;drl=sqrt(dr2);dsm(n1,n2)=drl;dsm(n2,n1)=drl;end
endupdate_plots;% --- Executes on button press in circle.
function circle_Callback(hObject, eventdata, handles)
global r nn dsm asznn=str2num(get(handles.nn,'string')); % number of citiesr=zeros(2,nn);% circle
al1=linspace(0,2*pi,nn+1);
al=al1(1:end-1);
r(1,:)=0.5*asz+0.45*asz*cos(al);
r(2,:)=0.5*asz+0.45*asz*sin(al);% r(1,:) -x coordinaties of cities
% r(2,:) -y coordinaties of citiesdsm=zeros(nn,nn); % matrix of distancies
for n1=1:nn-1r1=r(:,n1);for n2=n1+1:nnr2=r(:,n2);dr=r1-r2;dr2=dr'*dr;drl=sqrt(dr2);dsm(n1,n2)=drl;dsm(n2,n1)=drl;end
endupdate_plots;function nn_Callback(hObject, eventdata, handles)
update_plots_nn_ps;% --- Executes during object creation, after setting all properties.
function nn_CreateFcn(hObject, eventdata, handles)
% hObject    handle to nn (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    empty - handles not created until after all CreateFcns called% Hint: edit controls usually have a white background on Windows.
%       See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))set(hObject,'BackgroundColor','white');
endfunction ps_Callback(hObject, eventdata, handles)
update_plots_nn_ps;% --- Executes during object creation, after setting all properties.
function ps_CreateFcn(hObject, eventdata, handles)
% hObject    handle to ps (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    empty - handles not created until after all CreateFcns called% Hint: edit controls usually have a white background on Windows.
%       See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))set(hObject,'BackgroundColor','white');
end

四、运行结果

五、matlab版本及参考文献

1 matlab版本
2014a

2 参考文献
[1] 包子阳,余继周,杨杉.智能优化算法及其MATLAB实例（第2版）[M].电子工业出版社，2016.
[2]张岩,吴水根.MATLAB优化算法源代码[M].清华大学出版社，2017.

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