In this paper, we study the fruit fly in the fruit fly optimization algorithm (FOA) system moving in a quantum multi-dimensional space and propose a quantum behaved fruit fly optimization algorithm (QFOA) for the continuous function optimization problem. Computational experiments and comparisons are carried out based on a set of benchmark functions. The computational results show the advantage of QFOA to the original FOA.
CITATION STYLE
Zhang, X., & Xia, S. (2019). Quantum behaved fruit fly optimization algorithm for continuous function optimization problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11655 LNCS, pp. 331–340). Springer Verlag. https://doi.org/10.1007/978-3-030-26369-0_31
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