Swarm Intelligence (SI) techniques are more and more used by researchers in a wide range of areas: physics, economy, materials, biomedical sciences, computer sciences, engineering...
Recently, new published papers propose enhanced variant of SI techniques to improve the optimal solutions and achieve better results than other conventional optimization techniques, namely ACO, PSO, differential Evolution (DE)...
Does anyone have worked on these enhanced variant of SI techniques?
Regards.
Amin
Hi, are you aware of Fish School Search (FSS). Our newest version 'w' (i.e. wheited) is able to deal with very large continuous optimization problems, which present multiple modes (i.e. solutions). He is the pointer to the paper => LACERDA, Marcelo . Weight Based Fish School Search. In: IEEE SMC 2014 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, 2014, San Diego. Proceedings of IEEE SMC 2014
I have some experience in developing constrained versions of ACO and PSO and hybridizing them for better performance. You can find some of these works in my researchgate contributions.
Kindly, go through the following publication.
Y. del Valle, G. Venayagamoorthy, S. Mohagheghi, J.-C. Hernandez, R. Harley, Particle swarm optimization: Basic concepts, variants and applications in power systems, IEEE Transactions on Evolutionary Computation, 12 (2) (2008) 171-195.
I hope it will be very helpful to you.
codes are available here;
https://www.researchgate.net/publication/296636431_Codes_in_MATLAB_for_Particle_Swarm_Optimization?ev=prf_pub
Regards,
M.N.Alam
Code Codes in MATLAB for Particle Swarm Optimization
https://www.researchgate.net/publication/297245624_Particle_Swarm_Optimization_Algorithm_and_its_Codes_in_MATLAB
Research Particle Swarm Optimization: Algorithm and its Codes in MATLAB
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