A list,
1 Origin and development history of Ant Colony Algorithm (ACA) Marco Dorigo et al. found that ant colonies can quickly find targets by secreting biohormones called pheromones to communicate foraging information when searching for food. Therefore, in his doctoral dissertation in 1991, he first systematically proposed a new intelligent optimization algorithm “Ant System” (AS for short) based on Ant population. Later, the proposer and many researchers made various improvements to the algorithm and applied it to a wider range of fields. Figure coloring problem, secondary assignment problem, workpiece sequencing problem, vehicle routing problem, job shop scheduling problem, network routing problem, large-scale integrated circuit design and so on. In recent years, M.Dorigo et al. further developed Ant algorithm into a general Optimization technology “Ant Colony Optimization (ACO)”, and called all the algorithms conforming to ACO framework “ACO algorithm”.
Specifically, individual ants start looking for food without first telling them where it is. When an ant finds food, it releases a volatile pheromone (called a pheromone, it evaporates over time and its concentration indicates how far the path is) into the environment that other ants sense as a guide. Generally, when there are pheromones on multiple paths, the ant will preferentially choose the path with high pheromone concentration, so that the pheromone concentration of the path with high pheromone concentration will be higher, forming a positive feedback. Some ants do not repeat the same route as others. They take a different route. If the alternative path is shorter than the original one, gradually more ants are attracted to the shorter path. Finally, after some time of running, there may be a shortest path repeated by most ants. In the end, the path with the highest pheromone concentration is the optimal one selected by the ant.
Compared with other algorithms, ant colony algorithm is a relatively young algorithm, characteristics, such as distributed computing center control and asynchronous indirect communication between individuals, and is easy to be combined with other optimization algorithms, through many healthyenterprise continuously explore, to today has developed a variety of improved ant colony algorithm, but the principle of ant colony algorithm is still the main.
2. Solving principle of ant colony algorithm
Based on the above description of ant colony foraging behavior, the algorithm mainly simulates foraging behavior from the following aspects:
(1) The simulated graph scene contains two pheromones, one representing home and one representing food location, and both pheromones are volatilized at a certain rate.
(2) Each ant can perceive information only in a small part of the area around it. Ants searching for food, if within the scope of the perception, can directly in the past, if is beyond the scope of awareness, will be toward more than pheromones, ants can have a small probability pheromone many places don’t go, and instead, it is very important to the small probability event, represents a way of innovation, is very important to find a better solution.
(3) Ants return to the nest using the same rules as when they find food.
(4) When ants move, they will first follow the guidance of pheromone. If there is no guidance of pheromone, they will follow the direction of their moving inertia, but there is a certain probability of changing direction. Ants can also remember the path they have already walked, so as to avoid repeating the same place.
(5) The ants leave the most pheromones when they find food, and then the farther away they are from the food, the less pheromone they leave. The rules for finding nest pheromones are the same as for food. Ant colony algorithm has the following characteristics: positive feedback algorithm, concurrency algorithm, strong robustness, probabilistic global search, does not rely on strict mathematical properties, long search time, easy to stop phenomenon.
Ant transfer probability formula:
In the formula, is the probability of ant K transferring from city I to city J; α and β were the relative importance of pheromones and heuristic factors, respectively. Is the pheromone quantity on edge (I, j); Is the heuristic factor; The next step for Ant K allows the selection of cities. The above formula is the pheromone update formula in the ant system, and is the pheromone quantity on the edge (I,j). ρ is the evaporation coefficient of pheromone, 0<ρ<1; Is the pheromone quantity left by the KTH ant on the edge (I,j) in this iteration; Q is a normal coefficient; Is the path length of the k ant during this tour.
In ant system, pheromone update formula is:
3. Solving steps of ant colony algorithm:
(1) Initialization parameters At the beginning of calculation, it is necessary to initialize related parameters, such as ant colony size (ant number) m, pheromone importance factor α, heuristic function importance factor β, pheromone will emit money ρ, total pheromone release Q, maximum iteration times iter_max, initial value of iteration times iter=1.
(2) construct solution space and randomly place each ant at different starting points. For each ant k (k=1,2,3… M), calculate the next city to be visited according to (2-1) until all ants have visited all cities.
(3) update information su to calculate the path length of each ant Lk(k=1,2… , m), record the optimal solution (shortest path) in the current iteration number. At the same time, pheromone concentration on the connection path of each city was updated according to Equations (2-2) and (2-3).
(4) Determine whether to terminate if iter<iter_max, set iter=iter+1 to clear the record table of ant paths and return to Step 2; Otherwise, the calculation is terminated and the optimal solution is output.
(5) Determine whether to terminate if iter<iter_max, set iter=iter+1 to clear the record table of ant paths and return to Step 2; Otherwise, the calculation is terminated and the optimal solution is output. 3. Determine whether to terminate. If iter<iter_max, set iter=iter+1 to clear the record table of ant paths and return to Step 2. Otherwise, the calculation is terminated and the optimal solution is output.
Ii. Source code
function varargout = AntColonyVRPGUI(varargin)
% ANTCOLONYVRPGUI M-file for AntColonyVRPGUI.fig
% ANTCOLONYVRPGUI, by itself, creates a new ANTCOLONYVRPGUI or raises the existing
% singleton*.
%
% H = ANTCOLONYVRPGUI returns the handle to a new ANTCOLONYVRPGUI or the handle to
% the existing singleton*.
%
% ANTCOLONYVRPGUI('CALLBACK',hObject,eventData,handles,...) calls the local
% function named CALLBACK in ANTCOLONYVRPGUI.M with the given input arguments.
%
% ANTCOLONYVRPGUI('Property'.'Value',...). creates anew ANTCOLONYVRPGUI or raises the
% existing singleton*. Starting from the left, property value pairs are
% applied to the GUI before AntColonyVRPGUI_OpeningFcn gets called. An
% unrecognized property name or invalid value makes property application
% stop. All inputs are passed to AntColonyVRPGUI_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 AntColonyVRPGUI
% Last Modified by GUIDE v2. 5 11-Jun- 2015. 00:13:48
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @AntColonyVRPGUI_OpeningFcn, ...
'gui_OutputFcn', @AntColonyVRPGUI_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
% --- Executes just before AntColonyVRPGUI is made visible.
function AntColonyVRPGUI_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 AntColonyVRPGUI (see VARARGIN)
% Choose default command line output for AntColonyVRPGUI
handles.output = hObject;
%% change !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
handles.ismdvrp = true; %!!!!!! % %if handles.ismdvrp == true
[handles.initClusters, handles.coordinates] = INIT;
handles.clusters = handles.initClusters;
set(handles.uipanelBases,'Visible'.'on');
create_init_plot_MDVRP(handles.coordinates, handles.clusters);
else
%initialization
[vehicles,demands,dist_stations,dist_bases] = INIT_VRP;
handles.vehicles = vehicles;
handles.demands = demands;
handles.distances_stations = dist_stations;
handles.distances_bases = dist_bases;
set(handles.uipanelBases,'Visible'.'off');
end
% Update handles structure
guidata(hObject, handles);
% UIWAIT makes AntColonyVRPGUI wait for user response (see UIRESUME)
% uiwait(handles.figure1);
% --- Outputs from this function are returned to the command line.
function varargout = AntColonyVRPGUI_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 selection change in algorithmPopupmenu.
function algorithmPopupmenu_Callback(hObject, eventdata, handles)
% hObject handle to algorithmPopupmenu (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% Hints: contents = cellstr(get(hObject,'String')) returns algorithmPopupmenu contents as cell array
% contents{get(hObject,'Value')} returns selected item from algorithmPopupmenu
%set invisible error messages
set(handles.errorMandatoryEditFields,'Visible'.'off');
%erase text in edit fields
set(handles.evaporationPheromoneEdit,'String'."); set(handles.attractStationEdit,'String', '');
set(handles.increasePheromoneEdit,'String', '');
set(handles.amountPheromoneEdit,'String', '');
set(handles.eliteAntsEdit,'String', '');
%set disabled all edit fields
set(handles.evaporationPheromoneEdit,'Enable', 'off');
set(handles.attractStationEdit,'Enable', 'off');
set(handles.increasePheromoneEdit,'Enable', 'off');
set(handles.amountPheromoneEdit,'Enable', 'off');
set(handles.eliteAntsEdit,'Enable', 'off');
%set disabled run button
set(handles.runButton,'Enable', 'off');
%set to 0 all results
set(handles.lengthWayText,'String', '-');
set(handles.subroutesNText,'String', '-');
set(handles.timeSpentText,'String', '-'); if handles.ismdvrp == true %set invisible bases' listbox
set(handles.listboxBases,'Visible'.'off');
set(handles.totalLengthText,'Visible'.'off');
set(handles.totalLengthText,'String'.The '-');
set(handles.totalLengthLabel,'Visible'.'off');
%clear plot
cla;
create_init_plot_MDVRP(handles.coordinates, handles.clusters);
end
%clear plot
%cla;
%clear legend
legend('off');
val = get(hObject,'Value');
if val ~= 1 %not placeholder's text (not be executed) if val ~= 2 %not Clark-Wright algorithm %enable edit fields if val == 5 %AntAlg with elite ants set(handles.eliteAntsEdit,'Enable', 'on'); end set(handles.evaporationPheromoneEdit,'Enable', 'on'); set(handles.attractStationEdit,'Enable', 'on'); set(handles.increasePheromoneEdit,'Enable', 'on'); set(handles.amountPheromoneEdit,'Enable', 'on'); end %enable run button set(handles.runButton,'Enable', 'on'); end % --- Executes during object creation, after setting all properties. function algorithmPopupmenu_CreateFcn(hObject, eventdata, handles) % hObject handle to algorithmPopupmenu (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles empty - handles not created until after all CreateFcns called % Hint: popupmenu 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 evaporationPheromoneEdit_Callback(hObject, eventdata, handles) % hObject handle to evaporationPheromoneEdit (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 evaporationPheromoneEdit as text % str2double(get(hObject,'String')) returns contents of evaporationPheromoneEdit as a double % --- Executes during object creation, after setting all properties. function evaporationPheromoneEdit_CreateFcn(hObject, eventdata, handles) % hObject handle to evaporationPheromoneEdit (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 attractStationEdit_Callback(hObject, eventdata, handles) % hObject handle to attractStationEdit (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 attractStationEdit as text % str2double(get(hObject,'String')) returns contents of attractStationEdit as a double % --- Executes during object creation, after setting all properties. function attractStationEdit_CreateFcn(hObject, eventdata, handles) % hObject handle to attractStationEdit (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 increasePheromoneEdit_Callback(hObject, eventdata, handles) % hObject handle to increasePheromoneEdit (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 increasePheromoneEdit as text % str2double(get(hObject,'String')) returns contents of increasePheromoneEdit as a double % --- Executes during object creation, after setting all properties. function increasePheromoneEdit_CreateFcn(hObject, eventdata, handles) % hObject handle to increasePheromoneEdit (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 amountPheromoneEdit_Callback(hObject, eventdata, handles) % hObject handle to amountPheromoneEdit (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 amountPheromoneEdit as text % str2double(get(hObject,'String')) returns contents of amountPheromoneEdit as a double % --- Executes during object creation, after setting all properties. function amountPheromoneEdit_CreateFcn(hObject, eventdata, handles) % hObject handle to amountPheromoneEdit (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 eliteAntsEdit_Callback(hObject, eventdata, handles) % hObject handle to eliteAntsEdit (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 eliteAntsEdit as text % str2double(get(hObject,'String')) returns contents of eliteAntsEdit as a double % --- Executes during object creation, after setting all properties. function eliteAntsEdit_CreateFcn(hObject, eventdata, handles) % hObject handle to eliteAntsEdit (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 % --- Executes on button press in runButton. function runButton_Callback(hObject, eventdata, handles) % hObject handle to runButton (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) %clear legend legend('off'); %clear plot %cla; %set invisible error messages set(handles.errorMandatoryEditFields,'Visible', 'off'); indexAlg = get(handles.algorithmPopupmenu,'Value');
if indexAlg ~= 1 %not placeholder's text (not be executed)
if indexAlg ~= 2 %not Clark-Wright algorithm
if indexAlg == 5 %AntAlg with elite ants
if isempty(get(handles.eliteAntsEdit,'String'))
set(handles.errorMandatoryEditFields,'Visible'.'on');
return;
end
end
if ( isempty(get(handles.evaporationPheromoneEdit,'String') | |... isempty(get(handles.attractStationEdit,'String') | |... isempty(get(handles.increasePheromoneEdit,'String') | |... isempty(get(handles.amountPheromoneEdit,'String')))set(handles.errorMandatoryEditFields,'Visible'.'on');
return;
end
end
%set disabled run button
set(handles.runButton,'Enable'.'off');
if handles.ismdvrp == true
clusters = runAlgorithmMDVRP(indexAlg, handles);
handles.clusters = clusters;
listbox=findall(gcf,'tag'.'listboxBases');
guidata(listbox,handles);
%select first value in bases' listbox set(handles.listboxBases,'Value', 1); listboxBases_Callback(listbox, eventdata, handles); else runAlgorithmVRP(indexAlg, handles); end %set enabled run button set(handles.runButton,'Enable', 'on'); %set enabled zoom tools set(handles.toolZoomIn,'Enable', 'on'); set(handles.toolZoomOut,'Enable', 'on'); %set enabled pan tool set(handles.toolPan,'Enable', 'on'); zoom reset; end function [clusters] = runAlgorithmMDVRP(index, handles) if index ~= 1 if index ~= 2 e = str2double(get(handles.evaporationPheromoneEdit,'String')); alpha = str2double(get(handles.attractStationEdit,'String')); beta = str2double(get(handles.increasePheromoneEdit,'String')); tau0 = str2double(get(handles.amountPheromoneEdit,'String')); E = str2double(get(handles.eliteAntsEdit,'String')); end try tStart = tic; %start spent time clusters = handles.initClusters; handles.clusters = clusters; basesName = cell(1,length(clusters)+1); basesName{1} = 'Full view';
for c = 1:length(clusters)
switch index
case 2 %Clark-Wright
[ Route, RouteLength, vehicles ] = Clark_Wright_VRP( ...
clusters(c).demands, clusters(c).diststations, ...
clusters(c).distbases, clusters(c).vehicles_capacity );
case 3 %Ant-minpath
[Route, RouteLength, vehicles] = ANT_colony_algorithm_VRP_minpath( ...
clusters(c).diststations, clusters(c).distbases, ...
clusters(c).demands, [e alpha beta tau0], clusters(c).vehicles_capacity );
case 4 %Ant-partition
[Route, RouteLength, vehicles] = ANT_colony_algorithm_VRP( ...
clusters(c).diststations, clusters(c).distbases, ...
clusters(c).demands, [e alpha beta tau0], clusters(c).vehicles_capacity );
case 5 %Ant-elite ants
[Route, RouteLength, vehicles] = ANT_colony_algorithm_VRP_with_elite_ants( ...
clusters(c).diststations, clusters(c).distbases, ...
clusters(c).demands, [e alpha beta tau0 E], clusters(c).vehicles_capacity );
end
handles.clusters(c).mdvrp = changeStations(clusters, vehicles, RouteLength, Route, c);
basesName{c + 1} = sprintf('Base #%d',c); %saving bases that need to be added to listbox end tElapsed = toc(tStart); %end spent time catch ME msgbox(strcat('Error occured: ',ME.message),'Error', 'error'); end clusters = handles.clusters; %clear plot cla; create_plot_route_with_vehicles_MDVRP(handles.coordinates, handles.clusters); set(handles.timeSpentText,'String',sprintf('%fs',tElapsed)); set(handles.listboxBases, 'String', basesName); set(handles.listboxBases, 'Visible', 'on'); set(handles.totalLengthText,'String',num2str(getTotalLength(handles.clusters))); set(handles.totalLengthText,'Visible', 'on'); set(handles.totalLengthLabel,'Visible', 'on'); end function [mdvrp] = changeStations(clusters, vehicles, LR, R, clusterN) mdvrp = struct('length_route', [], 'vehicles', [], 'simpleVehicles', [], 'num_of_subroutes'[]); len = length(vehicles); mdvrp.simpleVehicles = vehicles; for v = 1:len vehicles(v).route(vehicles(v).route == 1) = 0; len_route = length(vehicles(v).route); The tendency of the youth to feel the infection (V).route(VR) = clusters(clusterN).stations(vehicles(v).route(vr)-1); end end end mdvrp.num_of_subroutes = number_of_subroutes(R); mdvrp.length_route = LR; mdvrp.vehicles = vehicles; function [tlength] = getTotalLength(clusters) tlength = 0; clen = length(clusters); for c = 1:clen tlength = tlength + clusters(c).mdvrp.length_route; end function runAlgorithmVRP(index, handles) if index ~= 1 if index ~= 2 e = str2double(get(handles.evaporationPheromoneEdit,'String')); alpha = str2double(get(handles.attractStationEdit,'String')); beta = str2double(get(handles.increasePheromoneEdit,'String')); tau0 = str2double(get(handles.amountPheromoneEdit,'String')); E = str2double(get(handles.eliteAntsEdit,'String')); end try tStart = tic; %start spent time switch index case 2 %Clark-Wright [Route,RouteLength,vehicles] = Clark_Wright_VRP( handles.demands, . handles.distances_stations, handles.distances_bases, handles.vehicles ); case 3 %Ant-minpath [Route,RouteLength,vehicles] = ANT_colony_algorithm_VRP_minpath( handles.distances_stations,... handles.distances_bases, handles.demands, [e alpha beta tau0], handles.vehicles); case 4 %Ant-partition [Route,RouteLength,vehicles] = ANT_colony_algorithm_VRP( handles.distances_stations, ... handles.distances_bases, handles.demands, [e alpha beta tau0], handles.vehicles); case 5 %Ant-elite ants [Route,RouteLength,vehicles] = ANT_colony_algorithm_VRP_with_elite_ants( ... handles.distances_stations, handles.distances_bases, handles.demands, ... [e alpha beta tau0 E], handles.vehicles); end tElapsed = toc(tStart); %end spent time create_plot_route_with_vehicles( add_bases_to_distances(handles.distances_stations, ... handles.distances_bases), vehicles, [0 handles.demands] ); catch ME msgbox(strcat('Error occured: ',ME.message),'Error', 'error'); end set(handles.lengthWayText,'String',num2str(RouteLength)); set(handles.subroutesNText,'String',num2str(number_of_subroutes(Route))); set(handles.timeSpentText,'String',sprintf('%fs',tElapsed)); end % -------------------------------------------------------------------- function dataTooltip_ClickedCallback(hObject, eventdata, handles) % hObject handle to dataTooltip (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % -------------------------------------------------------------------- function algorithmTooltip_ClickedCallback(hObject, eventdata, handles) % hObject handle to algorithmTooltip (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % --- Executes on selection change in listboxBases. function listboxBases_Callback(hObject, eventdata, handles) % hObject handle to listboxBases (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % Hints: contents = cellstr(get(hObject,'String')) returns listboxBases contents as cell array % contents{get(hObject,'Value')} returns selected item from listboxBases %clear legend legend('off'); %clear plot cla; index = get(handles.listboxBases,'value') - 1; if index == 0 %if user want to see the full graph of routes create_plot_route_with_vehicles_MDVRP(handles.coordinates, handles.clusters); set(handles.lengthWayText,'String', '-'); set(handles.subroutesNText,'String', '-'); else create_plot_of_base_MDVRP(handles.coordinates, handles.clusters, index); set(handles.lengthWayText,'String',num2str(handles.clusters(index).mdvrp.length_route)); set(handles.subroutesNText,'String',num2str(handles.clusters(index).mdvrp.num_of_subroutes)); end % --- Executes during object creation, after setting all properties. function listboxBases_CreateFcn(hObject, eventdata, handles) % hObject handle to listboxBases (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles empty - handles not created until after all CreateFcns called % Hint: listbox 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 aboutMenu_Callback(hObject, eventdata, handles)
% hObject handle to aboutMenu (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
About %call gui About.m
% --------------------------------------------------------------------
function fileMenu_Callback(hObject, eventdata, handles)
% hObject handle to fileMenu (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% --------------------------------------------------------------------
function anotherVRPSubmenu_Callback(hObject, eventdata, handles)
% hObject handle to anotherVRPSubmenu (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
% --------------------------------------------------------------------
function newDataSubmenu_Callback(hObject, eventdata, handles)
% hObject handle to newDataSubmenu (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)
Copy the code3. Operation results
Fourth, note
Version: 2014 a