Faster convergence often lead to sub optimal solutions. Is it possible to make the algorithm fast as well as more efficient in terms of attaining global minimum
Yes, its really true that effective boundary conditions lead to fast and efficient convergence in PSO.
I would like you have a look on the following articles shared on RG about PSO;
Research Particle Swarm Optimization: Algorithm and its Codes in MATLAB
Code Codes in MATLAB for Particle Swarm Optimization
Dear Nabab,
Thanks for sharing your article, it is good. A more detailed description on the effect of boundary conditions on convergence can be found in my article linked below:
http://dx.doi.org/10.1109/SSCI.2015.166
Do read it and give me your valuable feedback
Dear Dr. Mahamad Nabab Alam and Dr. Pragnan Chakravorty.
I am interested with this discussion. After see the article that previously shared. I come up with follow up question.
1. What about the boundary for Combinatorial Optimization Problem for example Travelling Salesman Problem or Vehicle Routing Problem.
2. What I understand that PSO is powerfull for continuous optimization problem and the boundary definition for continous optimization problem is pretty much simple and easy to define. How to effectively define boundary for integer and combinatiorial problem.
Hopefully this question can lead to a good discussion.
Best Regards,
Perwira Redi.
Dear Perwira,
Whether the problem is of combinatorial optimization or otherwise, the boundary properties of a particular optimization target (fitness/cost function) don't change; therefore, all the boundary algorithms discussed in my paper are equally applicable to all meta-heuristic optimization algorithms. Certainly, these boundary conditioning properties are expected to give better results.
Best Regards,
Pragnan
It depends on which kind of application you deal with. Ideally, yes it affect. However, it may also affect the quality of the solution itself.
Finally, you should test the PSO algorithm for different conditions to find the best answer.
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