Abstract
Firefly Algorithm (FA), a population based algorithm has been found superior over other algorithms in solving optimization problems. Later the authors formulated a quantum Delta potential well model for FA (QFA) by placing the fireflies in an exponent atmosphere with global updating operator and weighting function. In this paper, to improve the speed of convergence and provide a proper balance between local and global search ability of QFA, an interpolation based recombination operator for generating a new solution vector in the search space has been introduced. Above algorithm is compared with various other algorithms using several benchmark functions. Statistical performance using t-test on the results exhibits the superiority of proposed QFA.
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Manju, A., Nigam, M.J. (2014). An Improved Quantum Inspired Firefly Algorithm with Interpolation Operator. In: Pant, M., Deep, K., Nagar, A., Bansal, J. (eds) Proceedings of the Third International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 258. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1771-8_7
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DOI: https://doi.org/10.1007/978-81-322-1771-8_7
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