# Constraint handling in firefly algorithm

Published in 2013 IEEE international conference on cybernetics, 2013

Most of the contemporary bio-inspired optimization algorithms are formulated for unconstrained problems. Their performance may get affected when dealing with constrained problems. There is a number of constraint handling techniques developed for these algorithms. This paper intends to compare the performance of the emerging metaheuristic swarm optimization technique of Firefly Algorithm when incorporated with the generalized constrained handling techniques such as penalty function method, feasibility-based rule and the combination of both, i.e. combined approach. Seven well-known test problems have been solved. The results obtained using the three constraint handling techniques are compared and discussed with regard to the robustness, computational cost, rate of convergence, etc. The associated strengths, weaknesses and future research directions are also discussed.

• Recommended Citation:  @inproceedings{deshpande2013constraint, title={Constraint handling in firefly algorithm}, author={Deshpande, Aditya M and Phatnani, Gaurav Mohan and Kulkarni, Anand J}, booktitle={2013 IEEE international conference on cybernetics (CYBCO)}, pages={186--190}, year={2013}, organization={IEEE} }