【智能优化算法-海马优化器】基于海马优化器求解单目标优化问题附matlab代码

1 内容介绍

基于海马优化器求解单目标优化问题附matlab代码

2 部分代码

%_______________________________________________________________________________________%

%  Sea-Horse optimizer (SHO)

%  Developed in MATLAB R2018a

%  optimization problems.

%  Applied Intelligence

%_______________________________________________________________________________________%

clear all 

clc

close all

popsize=30; % Number of search agents

Max_iter=100; % Maximum iteration

F_name='F4'; % Name of the test function that can be from F1 to F23 (Table 2,3,4 in the paper)

[LB,UB,Dim,fobj]=BenchmarkFunctions(F_name);% Load details of the selected benchmark function

tic

[ObjectiveFitness,ObjectivePosition,Convergence_curve,Trajectories,fitness_history, population_history]=SHO(popsize,Max_iter,LB,UB,Dim,fobj);

time=toc;

figure('Position',[454   445   694   297]);

subplot(1,2,1);

func_plot(F_name);

title('Parameter space')

xlabel('x_1');

ylabel('x_2');

zlabel([F_name,'( x_1 , x_2 )'])

subplot(1,2,2);

semilogy(1:Max_iter,Convergence_curve,'color','r','linewidth',2.5);

title('Convergence curve');

xlabel('Iteration');

ylabel('Best score obtained so far')

display(['The running time is:', num2str(time)]);

display(['The best solution obtained by SHO is : ', num2str(ObjectiveFitness)]);

display(['The best optimal sea horse of the objective funciton found by SHO is : ', num2str(ObjectivePosition)]);

3 运行结果

4 参考文献

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