Abstract
Recent trend of research is to hybridize two and more algorithms to obtain superior solution in the field of optimization problems. In this context, a new method hybrid PSO (Particle Swarm Optimization)—MFO (Moth-Flame Optimizer) is exercised on some unconstraint benchmark test functions and overcurrent relay coordination optimization problems in contrast to test results on constrained/complex design problem. Hybrid PSO-MFO is combination of PSO used for exploitation phase and MFO for exploration phase in uncertain environment. Position and Velocity of particle is updated according to Moth and flame position in each iteration. Analysis of competitive results obtained from PSO-MFO validates its effectiveness compare to standard PSO and MFO algorithm.
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Bhesdadiya, R.H., Trivedi, I.N., Jangir, P., Kumar, A., Jangir, N., Totlani, R. (2017). A Novel Hybrid Approach Particle Swarm Optimizer with Moth-Flame Optimizer Algorithm. In: Bhatia, S., Mishra, K., Tiwari, S., Singh, V. (eds) Advances in Computer and Computational Sciences. Advances in Intelligent Systems and Computing, vol 553. Springer, Singapore. https://doi.org/10.1007/978-981-10-3770-2_53
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DOI: https://doi.org/10.1007/978-981-10-3770-2_53
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