Abstract
Shuffled frog leaping algorithm is one of the popular used optimization algorithms. This algorithm includes the local search and global search two solving modes, but in this method only the worst frog from divided group is considered for improving location. In this paper, we propose a directional shuffled frog leaping algorithm (DSFLA) by introducing the directional updating and real-time interacting concepts. A direction flag is set for a frog before moving, if the frog goes better in a certain direction, it will get better in a big probability by moving a little further along that direction. The movement counter is set for preventing the frog move forward infinite. Real-time interacting works by sharing the currently optimal positions from the other groups. There should have some similarities among the best ones, and the worst individual could be improved by using those similarities. The experimental results show that the proposed approach is a very effective method for solving test functions.
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Kong, L., Pan, JS., Chu, SC., Roddick, J.F. (2018). Directional Shuffled Frog Leaping Algorithm. In: Pan, JS., Wu, TY., Zhao, Y., Jain, L. (eds) Advances in Smart Vehicular Technology, Transportation, Communication and Applications. VTCA 2017. Smart Innovation, Systems and Technologies, vol 86. Springer, Cham. https://doi.org/10.1007/978-3-319-70730-3_31
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DOI: https://doi.org/10.1007/978-3-319-70730-3_31
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