【智能优化算法大合集】附matlab代码_适应度最小值算法综述资源-CSDN文库

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fig：1个

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智能优化算法是现代计算技术中一个重要的研究领域，它主要应用于解决复杂的优化问题，如工程设计、资源配置、机器学习模型的参数调优等。在MATLAB这个强大的数值计算环境中，智能优化算法得到了广泛的应用和实现。MATLAB 2019a版本提供了丰富的工具和函数，使得这些算法的开发和实验变得更加便捷。本资源包含的是一个【智能优化算法大合集】，特别适合于本科和硕士阶段的学生进行教研学习。以下是一些主要的智能优化算法及其在MATLAB中的应用要点： 1. 遗传算法（Genetic Algorithm, GA）：遗传算法是一种模拟生物进化过程的全局优化方法，通过选择、交叉和变异操作来搜索最优解。在MATLAB中，可以使用内置的`ga`函数实现遗传算法。 2. 蚁群算法（Ant Colony Optimization, ACO）：这是一种模拟蚂蚁寻找食物路径行为的优化算法，常用于解决旅行商问题等组合优化问题。MATLAB中虽然没有内置的ACO函数，但可以通过自定义函数实现。 3. 工蜂算法（Bee Colony Optimization, BCO）：模仿蜜蜂采蜜行为的算法，包括工蜂、侦查蜂和巢内蜂三种角色，适用于多模态优化问题。同样需要编写自定义代码来实现。 4. 避雷针算法（Lightning Search Algorithm, LSA）：灵感来源于雷电击中地面的概率分布，LSA具有快速收敛性和全局搜索能力，适用于求解连续优化问题。MATLAB中需自行编写算法代码。 5. 鲁棒优化算法（Robust Optimization）：针对不确定性和随机性，寻求对各种情况都有较好性能的解决方案。MATLAB提供了一些处理不确定性的工具箱，如Robust Control Toolbox，可以结合这些工具实现鲁棒优化。 6. 粒子群优化算法（Particle Swarm Optimization, PSO）：基于群体智慧的算法，通过粒子的飞行和速度更新寻找最优解。MATLAB中的`psodev`函数可以用来实现PSO。 7. 模拟退火算法（Simulated Annealing, SA）：模拟固体冷却过程中原子重排的过程，能够跳出局部最优，找到全局最优。MATLAB的全局优化工具箱提供了`simulannealbnd`和`simulannealintcon`函数。 8. 遗传编程（Genetic Programming, GP）：通过类似于生物进化的过程来演化程序，寻找解决问题的最佳表达。MATLAB的Global Optimization Toolbox提供了遗传编程的工具。 9. 灰狼优化算法（Grey Wolf Optimizer, GWO）：模拟灰狼群的狩猎策略进行优化，适用于多模态和非线性问题。需要自定义MATLAB代码实现。这些算法的学习和实践对于理解优化理论，提升编程能力，以及解决实际问题都有着重要的价值。在MATLAB环境下，不仅可以直观地看到算法的运行过程，还可以方便地调整参数，对比不同算法的效果，从而深入理解优化算法的原理和应用。对于科研和教学而言，这是一个非常宝贵的资源。

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【智能优化算法大合集】附matlab代码上传.zip （22个子文件）

【智能优化算法大合集】附matlab代码上传

Toolbox_all_algorithms

WOA

WOA.m 5KB

initialization.m 2KB

Optimization_toolbox.fig 37KB

MVO

MVO.m 7KB

RouletteWheelSelection.m 3KB

initialization.m 2KB

GWO

initialization.m 2KB

GWO.m 4KB

DA.m 8KB

Levy.m 2KB

distance.m 1KB

initialization.m 2KB

ALO

ALO.m 6KB

RouletteWheelSelection.m 2KB

initialization.m 2KB

Random_walk_around_antlion.m 3KB

MFO

MFO.m 6KB

initialization.m 2KB

SCA

SCA.m 5KB

initialization.m 2KB

CostFunction.m 2KB

Optimization_toolbox.m 17KB

function varargout = Optimization_toolbox(varargin) %___________________________________________________________________% % Optimization toolbox version 1.0 % % % % Developed in MATLAB R2011b(7.13) % % % % Author and programmer: Seyedali Mirjalili % % % % e-Mail: ali.mirjalili@gmail.com % % seyedali.mirjalili@griffithuni.edu.au % %___________________________________________________________________% % % % You can simply define your cost function in a seperate file. % The default name of the objective function is CostFunction. % If you have a look at the CostFunction.m file, you may notice % that the cost function gets the variables in a vector ([x1 x2 ... xn]) and % returns the objective value. You can either write you objective function % in this file or create a new file and pass its name to the toolbox. % Remember to follow the same structure for input and output if you decided % to go for the second option. % % The lower bounds and upper bounds of variables should also be witten as % lb1,lb2,...,lbn and ub1,ub2,...,ubn % % If all of the variables have equal lower and/or upper bounds you can just % define lb and ub as two single number numbers: lb, ub % Begin initialization code - DO NOT EDIT gui_Singleton = 1; gui_State = struct('gui_Name', mfilename, ... 'gui_Singleton', gui_Singleton, ... 'gui_OpeningFcn', @Optimization_toolbox_OpeningFcn, ... 'gui_OutputFcn', @Optimization_toolbox_OutputFcn, ... 'gui_LayoutFcn', [] , ... 'gui_Callback', []); if nargin && ischar(varargin{1}) gui_State.gui_Callback = str2func(varargin{1}); end if nargout [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); else gui_mainfcn(gui_State, varargin{:}); end % End initialization code - DO NOT EDIT addpath('./GWO') addpath('./ALO') addpath('./MVO') addpath('./DA') addpath('./MFO') addpath('./SCA') addpath('./WOA') % --- Executes just before Optimization_toolbox is made visible. function Optimization_toolbox_OpeningFcn(hObject, eventdata, handles, varargin) % This function has no output args, see OutputFcn. % hObject handle to figure % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % varargin command line arguments to Optimization_toolbox (see VARARGIN) % Choose default command line output for Optimization_toolbox handles.output = hObject; % Update handles structure guidata(hObject, handles); % UIWAIT makes Optimization_toolbox wait for user response (see UIRESUME) % uiwait(handles.figure1); % --- Outputs from this function are returned to the command line. function varargout = Optimization_toolbox_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; labelStr = '<html><center><a href="">alimirjalili.com'; cbStr = 'web(''http://www.alimirjalili.com'');'; hButton = uicontrol('string',labelStr,'pos',[150,20,100,35],'callback',cbStr); labelStr = '<html><center><a href="">Find the papers'; cbStr = 'web(''http://alimirjalili.com/Publication.html'');'; hButton = uicontrol('string',labelStr,'pos',[50,20,100,35],'callback',cbStr); function WolfNo_Callback(hObject, eventdata, handles) % hObject handle to WolfNo (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % Hints: get(hObject,'String') returns contents of WolfNo as text % str2double(get(hObject,'String')) returns contents of WolfNo as a double % --- Executes during object creation, after setting all properties. function WolfNo_CreateFcn(hObject, eventdata, handles) % hObject handle to WolfNo (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 function IterNo_Callback(hObject, eventdata, handles) % hObject handle to IterNo (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % Hints: get(hObject,'String') returns contents of IterNo as text % str2double(get(hObject,'String')) returns contents of IterNo as a double % --- Executes during object creation, after setting all properties. function IterNo_CreateFcn(hObject, eventdata, handles) % hObject handle to IterNo (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 function LowerBound_Callback(hObject, eventdata, handles) % hObject handle to LowerBound (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % Hints: get(hObject,'String') returns contents of LowerBound as text % str2double(get(hObject,'String')) returns contents of LowerBound as a double % --- Executes during object creation, after setting all properties. function LowerBound_CreateFcn(hObject, eventdata, handles) % hObject handle to LowerBound (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 function UpperBound_Callback(hObject, eventdata, handles) % hObject handle to UpperBound (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % Hints: get(hObject,'String') returns contents of UpperBound as text % str2double(get(hObject,'String')) returns contents of UpperBound as a double % --- Executes during object creation, after setting all properties. function UpperBound_CreateFcn(hObject, eventdata, handles) % hObject handle to UpperBound (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 function Dim_Callback(hObject, eventdata, handles) % hObject handle to Dim (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % Hints: get(hObject,'String') returns contents of Dim as text % str2double(get(hObject,'String')) ret

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