HLO
%% Description % 1.A MATLAB code for Human Learning Optimization(HLO) algorithm [1] is developed for a simple test problems in this file. % 2.Main program of HLO which is "SHLO.m",and HLO code is tested and verified for a simple problem. % 3.Anybody can use this code for their application, by developing their own fitness function for the unique problems. % 4.For any new test problem (application), the following modifications are sufficient.They are listed down. % 5.For complicated problems, it is better to introudce the re-learning operator given in [2] to obtain better results. % 6.There is an adaptive simplified HLO in [3],which change the mode of 'pr'and 'pi'.
%% Problem Dependent variables
% popsize % Population size
% runtimes % Number of runs
% Gmax % Mzx number of generations - stopping criteria
% Dim=2; %Variable number
% bit=30; %Bits numbers
% Xmax=100; %Vaiable range
% Xmin=-100; %Vaiable range
% load sphere_func_data.mat %Test different function need change this files
%% Test problem
% Evfit %Fitness function
%% References: % 1.Ling Wang, Haoqi Ni, Ruixin Yang, Minrui Fei, Wei Ye. A Simple Human Learnibg Optimization Algorithm. % Communications in Computer and Information Science. 2014,v462:56-65 % 2.Ling Wang, Ruixin Yang, Haoqi Ni, Wei Ye, Minrui Fei, and Panos M. Pardalos. A Human Learning Optimization % Algorithm and Its Application to Multi-dimensional Knapsack Problems. Applied Soft Computing. 2015,34:736-743 % 3.Ling Wang, Haoqi Ni, Ruixin Yang, Panos M. Pardalos, Xin Du, Minrui Fei. An Adaptive Simplified Human % Learning Optimization Algorithm. Information Sciences. 2015,320:126-139