CHPSO优化算法matlab源码程序 - matlab算法设计

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标题：CHPSO优化算法matlab源码程序
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所属分类: 算法设计资源类型：文件大小: 4.89 KB 上传时间: 2016-01-24 21:43:18 下载次数: 5 资源积分：1分提供者: 马云 CHPSO优化算法matlab源码程序

内容：
CHPSO优化算法matlab源码程序，程序员在编程的过程中可以参考学习使用，希望对IT程序员有用，此源码程序简单易懂、方便阅读，有很好的学习价值！

部分代码如下：

function varargout = CHPSO_func(fhd,numIter,param,varargin)

format short e

% make copies of parameters

NP = param.ParicleNumber;

acc = param.AccelerationConstants;

iwt = param.InteriaWeight;

dim = param.Dimension;

Ub = param.Ub;

Lb = param.Lb;

mv = repmat(0.5*(Ub-Lb),1,dim);

w_max = iwt(1);

w_min = iwt(2);

pos_a = Lb+(Ub-Lb).*rand(NP,dim);

pos_b = Lb+(Ub-Lb).*rand(NP,dim);

pos_c = Lb+(Ub-Lb).*rand(NP,dim);

pos_d = Lb+(Ub-Lb).*rand(NP,dim);

vel_a = Lb+(Ub-Lb).*rand(NP,dim);

vel_b = Lb+(Ub-Lb).*rand(NP,dim);

vel_c = Lb+(Ub-Lb).*rand(NP,dim);

vel_d = Lb+(Ub-Lb).*rand(NP,dim);

for j = 1:NP

val_a(j,1) = feval(fhd,pos_a(j,:),varargin{:});

val_b(j,1) = feval(fhd,pos_b(j,:),varargin{:});

val_c(j,1) = feval(fhd,pos_c(j,:),varargin{:});

val_d(j,1) = feval(fhd,pos_d(j,:),varargin{:});

end

localPos_a = pos_a; localVal_a = val_a;

localPos_b = pos_b; localVal_b = val_b;

localPos_c = pos_c; localVal_c = val_c;

localPos_d = pos_d; localVal_d = val_d;

[gval_a, idx_a] = min(val_a(:,1)); globalPos_a = pos_a(idx_a,:);

[gval_b, idx_b] = min(val_b(:,1)); globalPos_b = pos_b(idx_b,:);

[gval_c, idx_c] = min(val_c(:,1)); globalPos_c = pos_c(idx_c,:);

[gval_d, idx_d] = min(val_d(:,1)); globalPos_d = pos_d(idx_d,:);

G = [globalPos_a; globalPos_b; globalPos_c; globalPos_d];

[gVal, idx] = min([gval_a; gval_b; gval_c; gval_d]);

globalPos = G(idx,:);

% best record

BestChart = [];

BestChart = [BestChart; gVal];

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

rfc = 0; RFC = 2;

for i = 2:numIter

fit_avg = (sum(val_a(:,1))+sum(val_b(:,1))+sum(val_c(:,1))+sum(val_d(:,1)))/(4*NP);

fit_m = [min(val_a(:,1)),min(val_b(:,1)),min(val_c(:,1)),min(val_d(:,1))];

fit_min = min(fit_m);

for j = 1:NP

w = w_max-(w_max-w_min)*i/numIter;

vel_a(j,:) = w.*vel_a(j,:)+acc(1).*rand.*(localPos_a(j,1:dim)-pos_a(j,1:dim))...

+acc(2).*rand.*(globalPos(1:dim)-pos_a(j,1:dim));

vel_a(j,:) = (vel_a(j,:)>mv).*mv+(vel_a(j,:)<=mv).*vel_a(j,:);

vel_a(j,:) = (vel_a(j,:)<(-mv)).*(-mv)+(vel_a(j,:)>=(-mv)).*vel_a(j,:);

pos_a(j,1:dim) = pos_a(j,1:dim)+vel_a(j,1:dim);

val_a(j,1) = feval(fhd,pos_a(j,1:dim),varargin{:});

vel_b(j,:) = w.*vel_b(j,:)+acc(1).*rand.*(localPos_b(j,1:dim)-pos_b(j,1:dim))...

+acc(2).*rand.*(globalPos(1:dim)-pos_b(j,1:dim));

vel_b(j,:) = (vel_b(j,:)>mv).*mv+(vel_b(j,:)<=mv).*vel_b(j,:);

vel_b(j,:) = (vel_b(j,:)<(-mv)).*(-mv)+(vel_b(j,:)>=(-mv)).*vel_b(j,:);

pos_b(j,1:dim) = pos_b(j,1:dim)+vel_b(j,1:dim);

val_b(j,1) = feval(fhd,pos_b(j,1:dim),varargin{:});

gama1 = val_a(j,1);

gama2 = val_b(j,1);

gama = val_a(j,1)+val_b(j,1);

vel_c(j,:) = w.*((gama.*vel_a(j,:)/gama1+gama.*vel_b(j,:)/gama2)+vel_c(j,:))...

+acc(1).*rand.*(localPos_c(j,1:dim)-pos_c(j,1:dim))...

+acc(2).*rand.*(globalPos(1:dim)-pos_c(j,1:dim));

vel_c(j,:) = (vel_c(j,:)>mv).*mv+(vel_c(j,:)<=mv).*vel_c(j,:);

vel_c(j,:) = (vel_c(j,:)<(-mv)).*(-mv)+(vel_c(j,:)>=(-mv)).*vel_c(j,:);

pos_c(j,1:dim) = pos_c(j,1:dim)+vel_c(j,1:dim);

val_c(j,1) = feval(fhd,pos_c(j,1:dim),varargin{:});

vel_d(j,:)=(vel_a(j,:)+vel_b(j,:)-vel_c(j,:));

vel_d(j,:) = (vel_d(j,:)>mv).*mv+(vel_d(j,:)<=mv).*vel_d(j,:);

vel_d(j,:) = (vel_d(j,:)<(-mv)).*(-mv)+(vel_d(j,:)>=(-mv)).*vel_d(j,:);

pos_d(j,1:dim) = pos_d(j,1:dim)./6+localPos_d(j,1:dim)./3+globalPos(1,1:dim)./2+vel_d(j,1:dim);

val_d(j,1) = feval(fhd,pos_d(j,1:dim),varargin{:});

if (val_a(j,1)<localVal_a(j,1))

localPos_a(j,:) = pos_a(j,:);

localVal_a(j,1) = val_a(j,1);

end

if (val_b(j,1)<localVal_b(j,1))

localPos_b(j,:) = pos_b(j,:);

localVal_b(j,1) = val_b(j,1);

end

if (val_c(j,1)<localVal_c(j,1))

localPos_c(j,:) = pos_c(j,:);

localVal_c(j,1) = val_c(j,1);

end

if (val_d(j,1)<localVal_d(j,1))

localPos_d(j,:) = pos_d(j,:);

localVal_d(j,1) = val_d(j,1);

end

[gval_a, idx_a] = min(val_a(:,1));

[gval_b, idx_b] = min(val_b(:,1));

[gval_c, idx_c] = min(val_c(:,1));

[gval_d, idx_d] = min(val_d(:,1));

globalPos_a = pos_a(idx_a,:);

globalPos_b = pos_b(idx_b,:);

globalPos_c = pos_c(idx_c,:);

globalPos_d = pos_d(idx_d,:);

[gVal_tmp idx] = min([gval_a; gval_b; gval_c; gval_d]);

G = [globalPos_a; globalPos_b; globalPos_c; globalPos_d];

if gVal_tmp<gVal

globalPos = G(idx,:);

gVal = gVal_tmp;

end

BestChart = [BestChart; gVal];

rfc = rfc+1;

if rfc >= RFC

rfc = 0;

[wval_a, b_index1] = max(val_a(:,1));

[wval_b, b_index2] = max(val_b(:,1));

[wval_c, b_index3] = max(val_c(:,1));

[wval_d, b_index4] = max(val_d(:,1));

pos_a(b_index1,:) = -globalPos;

pos_b(b_index2,:) = -globalPos;

pos_c(b_index3,:) = -globalPos;

pos_d(b_index4,:) = -globalPos;

end

varargout{1} = BestChart;

文件列表（点击上边下载按钮，如果是垃圾文件请在下面评价差评或者投诉）:

CHPSO优化算法matlab源码程序/
CHPSO优化算法matlab源码程序/CHPSO/
CHPSO优化算法matlab源码程序/CHPSO/CHPSO.m
CHPSO优化算法matlab源码程序/CHPSO/CHPSO_func.m
CHPSO优化算法matlab源码程序/CHPSO/funcRange.m
CHPSO优化算法matlab源码程序/CHPSO/objFunc.m

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