Bat algorithm (demo)
This is a short demo for the popular, nature-inspired/metaheuristic,
bat algorithm (BA), which can deal with nonlinear, global optimization problems.
Bat algorithm has the advantages of simplicity, flexility and stability.
It can also automatically switch from global exploration to
local exploitation by fine-tuning its parameters: A and r.
The paper can be downloaded at
http://arxiv.org/abs/1004.4170
Cite As
Xin-She Yang (2020). Bat algorithm (demo) (https://www.mathworks.com/matlabcentral/fileexchange/37582-bat-algorithm-demo), MATLAB Central File Exchange. Retrieved .
Comments and Ratings (44)
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Thank you very much Dr. Yang, but I've been trying to write a Matlab code following the steps provided by your book, and I have found that the rate of pulse emission should increase with iterations, but it's decreasing in the code!!!
another important thing is why to link the choosing of new better solution with a decreasing probability!!
hello,
The BAT algorithm Source Code , do not converge for any benchMark function!!
The complete implementation of BAT algorithm is available at https://in.mathworks.com/matlabcentral/fileexchange/68981-bat-optimization-algorithm
Hello Prof Xin-She Yang
How to hybridize BAT algorithm with Moth-Flame Optimization Algorithm if you have them in different scripts.
email: djiddosaid@gmail.com
Thank you so much
dear proffesor,
I am very interested in bat algorithm and decided to use it in my final year project for improvement in global optimazation problems.
can you send the bat algorithm code to me so that i could study it. Thank you.
email: suhadasaffie95@gmail.com
please someone explain why we have chosen here dimension d & what it indicates.
hello,
I did not understand this code. Can't we create an environment and view the shortest path like in Probabilistic Road Map (PRM)?
And what does the dimension mean in this code?
Please help me..
if (Fnew<=Fitness(i)) & (rand<A) ,
Sol(i,:)=S(i,:);
Fitness(i)=Fnew
end
Why accept a better solution with a certain probability? And This probability becomes smaller and smaller as the number of iterations increases
Thank you for your share of Dr. Yang.
if (rand < Ai & f(xi) < f(x))
Accept the new solutions
Increase ri and reduce Ai
end if
in the article of Dr. Yang, but the code is different. I need a great code of Matlab . Thank you! 263211434@qq.com
I noticed that problem as well. Your solution seems to work, though it would have been great if Dr. Yang could provide with a formal solution. 835441346@qq.com
I want a solution matlab code modified bat algorithm
Hello..can u plz help to write a code for minimize the total cost.actually my Ain is allocation of battery in microgrid.and I am extremely new in MATLAB.
i want bat algorithm and code for clustering in java.........
Dear Prof
Im a maths student an I have found Bat algorithm to interesting would like so much to know if the Bat Inspired algorithm can be of any use in the fields of Electrical distribution and Transmission.
Email:2016sors@gmail.com
akradore@gmail.com
dear prof
I am very interested in bat algorithm.
can you send the bat algorithm code to me?
e-mail
zhenli_ysu@126.com
thank you
dear prof
can you help me with chaotic bat algorithm code ??
e-mail
eng.daliaarafa@gmail.com
thanks in advance
I Have a Question. Everytime I run this algorithm, I get different sets of solutions every time. Why is it so? Shouldn't there be a unique solution for a given problem? Plz Help.
Hello
@ Eric : In the article published by Dr. Yang, he did not specify that “epsilon” must be a uniform random number.
Comparing the proposed demo and the pseudo-code presented in the article of Dr. Yang, I noticed this:
In the article: if (rand < Ai & f(xi) < f(x*)) and x* is the current global best location (solution) which is located after comparing all the solutions among all the n bats. But, in the demo,
if (Fnew<=Fitness(i)) & (rand<A),
Sol(i,:)=S(i,:);
Fitness(i)=Fnew;
end
I understand from this that for each bat, we do a comparaison between the new calculated fitness values against the previous one, not against the global best. Then, each bat memorises his "individual" best location and update it according to the condition mentionned above. I hope that i will have clarification about this.
There are three discrepancies in this code (compared to the published algorithm)
1. Line 79
Q(i)=Qmin+(Qmin-Qmax)*rand;
should be replaced with
Q(i)=Qmin+(Qmax-Qmin)*rand;
2. Similar to what @Frank said
Line 83
Sol(i,:)=simplebounds(Sol(i,:),Lb,Ub);
should be replaced with
S(i,:)=simplebounds(S(i,:),Lb,Ub);
and moved to Line 89 (*before* %Evaluate Evaluate new solutions)
3. Line 87
S(i,:)=best+0.001*randn(1,d);
The 2010 paper "A New Metaheuristic Bat-Inspired Algorithm" seems to suggest that 0.001 should be the variable "A" and that randn(1,d) should actually be 1-2*rand(1,d)... that is a uniformly distributed random number bounded by [-1,1].
@Frank,
I noticed that problem as well. Your solution seems to work, though it would have been great if Dr. Yang could provide with a formal solution.
Hello
I have my Objective function and constraint, anyone can help me to guide me on how implement it.
Actually mu purpose is reduce electric distribution loss.
It is good.
Would this line of code in bat_algorithm.m:
% Apply simple bounds/limits
Sol(i,:)=simplebounds(Sol(i,:),Lb,Ub);
be moved to just above the line of
% Evaluate new solutions
and be modified to:
S(i,:)=simplebounds(S(i,:),Lb,Ub);
so that we may not have solutions outside the lower and upper bound?
Easy to understand...
Very easy to understand but works magic.
It is easy to understand, and it works magic. Excellent!
simple and easy of use.... thanks
I am interest in your optimization algorithm. May i know is there a 'train' function coded because I would want to use it to train neural network.
Thank you.
Hi plz anyone can guide how to train Neural Network using Bat algorithm????
also how to get graphs for bat algorithm..?
hey i want to compare cuckoo search and bat algorithm.. can you tell me on what parameters should i compare them..
It is very good.
It is easy to understand, and it works magic. Excellent!