Is particle swarm optimization yields better solution in solving MINLP problem compare to classical methods?
comparison with respect to the following
i) optimality
ii) computational time
iii) with inclusion of integer, binary and continuous variables
Dear Sir,
Performance of Classical Methods are highly depended on the characteristics of solution-space. Most of the real-world MINLP problems have very complex solution-space (highly multi-modal, dis-continuous etc). If a classical methods fail to provide solution then PSO is a better option. Generally, classical methods are faster then PSO in terms of convergence but classical methods have very limitations and cannot be applied to every MINLP problems. Therefore, in general, PSO is better than classical methods only in terms of limitations of solvability.
Thank you Abhishek. I have one more question, If MINLP convert to MILP problem, in this case classical optimisation leads to global optimal solution compare to PSO?
Absolutely yes, the classic methods are much better
https://www.udemy.com/gamsoptimization/?couponCode=GAMS2018DISCOUNTED
Deterministic algorithms (classical methods) follow a rigorous procedure to detect the optimum point, on other hand, the stochastic algorithms are characterized by some randomness to reach optimality
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