1 算法介绍
2 部分代码
% 清除环境变量
close all
clc; clear
%% Problem Statement
ProblemParams.CostFuncName = 'fitcal'; % You should state the name of your cost function here.
ProblemParams.CostFuncExtraParams = [];
ProblemParams.NPar = 31; % Number of optimization variables of your objective function. "NPar" is the dimention of the optimization problem.
ProblemParams.VarMin = -1; % Lower limit of the optimization parameters. You can state the limit in two ways. 1) 2)
ProblemParams.VarMax = 1; % Lower limit of the optimization parameters. You can state the limit in two ways. 1) 2)
% Modifying the size of VarMin and VarMax to have a general form
if numel(ProblemParams.VarMin)==1 %numel 数组元素个数计数
ProblemParams.VarMin=repmat(ProblemParams.VarMin,1,ProblemParams.NPar); %复制矩阵，行数不变，仍然是roblemParams.VarMin，列数重复ProblemParams.NPar遍ProblemParams.VarMin
ProblemParams.VarMax=repmat(ProblemParams.VarMax,1,ProblemParams.NPar);
end
ProblemParams.SearchSpaceSize = ProblemParams.VarMax - ProblemParams.VarMin; %搜索区间
%% Algorithmic Parameter Setting
AlgorithmParams.NumOfCountries = 200; % Number of initial countries.
AlgorithmParams.NumOfInitialImperialists = 10; % Number of Initial Imperialists.
AlgorithmParams.NumOfAllColonies = AlgorithmParams.NumOfCountries - AlgorithmParams.NumOfInitialImperialists;
AlgorithmParams.NumOfDecades = 100; %迭代次数
AlgorithmParams.RevolutionRate = 0.3; % Revolution is the process in which the socio-political characteristics of a country change suddenly.
AlgorithmParams.AssimilationCoefficient = 2; % In the original paper assimilation coefficient is shown by "beta". 每次趋近的系数
AlgorithmParams.AssimilationAngleCoefficient = .5; % In the original paper assimilation angle coefficient is shown by "gama". 夹角度数
AlgorithmParams.Zeta = 1; % Total Cost of Empire = Cost of Imperialist + Zeta * mean(Cost of All Colonies);
AlgorithmParams.DampRatio = 0.99;
AlgorithmParams.StopIfJustOneEmpire = false; % Use "true" to stop the algorithm when just one empire is remaining. Use "false" to continue the algorithm. 停止迭代的标志
AlgorithmParams.UnitingThreshold = 0.0001; % The percent of Search Space Size, which enables the uniting process of two Empires.
zarib = 1.05; % **** Zarib is used to prevent the weakest impire to have a probability equal to zero
alpha = 0.03; % **** alpha is a number in the interval of [0 1] but alpha<<1. alpha denotes the importance of mean minimum compare to the global mimimum.
%% Display Setting
DisplayParams.PlotEmpires = true; % "true" to plot. "false" to cancel ploting. 殖民者参数
if DisplayParams.PlotEmpires
DisplayParams.EmpiresFigureHandle = figure('Name','Plot of Empires','NumberTitle','off');
DisplayParams.EmpiresAxisHandle = axes;
end
DisplayParams.PlotCost = true; % "true" to plot. "false" 消耗参数
if DisplayParams.PlotCost
DisplayParams.CostFigureHandle = figure('Name','Plot of Minimum and Mean Costs','NumberTitle','off');
DisplayParams.CostAxisHandle = axes;
end
ColorMatrix = [1 0 0 ; 0 1 0 ; 0 0 1 ; 1 1 0 ; 1 0 1 ; 0 1 1 ; 1 1 1 ;
0.5 0.5 0.5; 0 0.5 0.5 ; 0.5 0 0.5 ; 0.5 0.5 0 ; 0.5 0 0 ; 0 0.5 0 ; 0 0 0.5 ;
1 0.5 1 ; 0.1*[1 1 1]; 0.2*[1 1 1]; 0.3*[1 1 1]; 0.4*[1 1 1]; 0.5*[1 1 1]; 0.6*[1 1 1]];
DisplayParams.ColorMatrix = [ColorMatrix ; sqrt(ColorMatrix)]; %sqrt 平方根，什么用？
DisplayParams.AxisMargin.Min = ProblemParams.VarMin;
DisplayParams.AxisMargin.Max = ProblemParams.VarMax;
%%
for i=1
%% Creation of Initial Empires
InitialCountries = GenerateNewCountry(AlgorithmParams.NumOfCountries , ProblemParams);%建立国家 子函数调用 一个列向量 (AlgorithmParams.NumOfCountriesx1) 值为约束范围内的随机数
% Calculates the cost of each country. The less the cost is, the more is the power.
if isempty(ProblemParams.CostFuncExtraParams)
InitialCost = feval(ProblemParams.CostFuncName,InitialCountries);
else
InitialCost = feval(ProblemParams.CostFuncName,InitialCountries,ProblemParams.CostFuncExtraParams);
end
[InitialCost,SortInd] = sort(InitialCost); % Sort the cost in assending order. The best countries will be in higher places 排序 每行从小到大
InitialCountries = InitialCountries(SortInd,:); % Sort the population with respect to their cost. 按照相关耗费给国家排序
%stop 调试所用
Empires = CreateInitialEmpires(InitialCountries,InitialCost,AlgorithmParams, ProblemParams);%子函数调用 得到帝国种群（殖民国加殖民地）
%% Main Loop
MinimumCost = repmat(nan,AlgorithmParams.NumOfDecades,1); %把nan复制了AlgorithmParams.NumOfDecades次，一个超长的列向量
MeanCost = repmat(nan,AlgorithmParams.NumOfDecades,1);
if DisplayParams.PlotCost
axes(DisplayParams.CostAxisHandle);
if any(findall(0)==DisplayParams.CostFigureHandle)
h_MinCostPlot=plot(MinimumCost,'r','LineWidth',1.5,'YDataSource','MinimumCost');
hold on;
h_MeanCostPlot=plot(MeanCost,'k:','LineWidth',1.5,'YDataSource','MeanCost');
hold off;
pause(0.05);
end
end
for Decade = 1:AlgorithmParams.NumOfDecades
AlgorithmParams.RevolutionRate = AlgorithmParams.DampRatio * AlgorithmParams.RevolutionRate;%进化率=0.99*原进化率
Remained = AlgorithmParams.NumOfDecades - Decade
for ii = 1:numel(Empires)
%% Assimilation同化; Movement of Colonies Toward Imperialists (Assimilation Policy)
Empires(ii) = AssimilateColonies(Empires(ii),AlgorithmParams,ProblemParams);%子函数调用
%% Revolution; A Sudden Change in the Socio-Political Characteristics 有部分用重新生成的国家替代
Empires(ii) = RevolveColonies(Empires(ii),AlgorithmParams,ProblemParams);%子函数调用
%% New Cost Evaluation
if isempty(ProblemParams.CostFuncExtraParams)
Empires(ii).ColoniesCost = feval(ProblemParams.CostFuncName,Empires(ii).ColoniesPosition);
else
Empires(ii).ColoniesCost = feval(ProblemParams.CostFuncName,Empires(ii).ColoniesPosition,ProblemParams.CostFuncExtraParams);
end
%% Empire Possession (****** Power Possession, Empire Possession)
Empires(ii) = PossesEmpire(Empires(ii));%子函数调用
%% Computation of Total Cost for Empires
Empires(ii).TotalCost = Empires(ii).ImperialistCost + AlgorithmParams.Zeta * mean(Empires(ii).ColoniesCost);
end
%% Uniting Similiar Empires
Empires = UniteSimilarEmpires(Empires,AlgorithmParams,ProblemParams);%子函数调用
%% Imperialistic Competition
Empires = ImperialisticCompetition(Empires);%子函数调用
if numel(Empires) == 1 && AlgorithmParams.StopIfJustOneEmpire%如果只剩下一个殖民者
break
end
%% Displaying the Results
DisplayEmpires(Empires,AlgorithmParams,ProblemParams,DisplayParams);%子函数调用
ImerialistCosts = [Empires.ImperialistCost];
[MinimumCost(Decade),index] = min(ImerialistCosts);% 调试 MinimumCost(Decade) = min(ImerialistCosts);
MeanCost(Decade) = mean(ImerialistCosts);
%% 导出
if Decade == AlgorithmParams.NumOfDecades
positions(i,:)=[Empires(index).ImperialistPosition ];
results(i,:)=[MinimumCost(Decade)];
end
if DisplayParams.PlotCost
refreshdata(h_MinCostPlot);
% refreshdata(h_MeanCostPlot);
drawnow; grid on;hold on;
xlabel('迭代代数/次');ylabel('目标函数值');
pause(0.01);
end
% if DisplayParams.PlotCost
% refreshdata(h_MinCostPlot);%刷新图片的数据
% refreshdata(h_MeanCostPlot);
% drawnow;grid on;hold on;
% xlabel('迭代代数/次');ylabel('目标函数值');
% pause(0.01);
% end
end % End of Algorithm
%%
end
MinimumCost(end)
save Cost MinimumCost
save pos positions
3 仿真结果
4 参考文献
[1]张镱议,焦健,汪可,郑含博,房加珂,周浩.基于帝国殖民竞争算法优化支持向量机的电力变压器故障诊断模型[J].电力自动化设备,2018,38(01):99-104.
5 MATLAB代码与数据下载地址
见博客主页
