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EURASIP Journal on Wireless Communications and Networking
Fig. 2 | EURASIP Journal on Wireless Communications and Networking

Fig. 2

From: A bi-population QUasi-Affine TRansformation Evolution algorithm for global optimization and its application to dynamic deployment in wireless sensor networks

Fig. 2

Fitness errors vs. number of function evaluations of functions f8, f12, f15, and f24. The figure presents the fitness error and the convergence speed comparison by employing the best value of 50 runs obtained by each competing algorithm on 30-D optimization. The functions f8, f12, f15, and f24 figures are presented here. NFE means number of function evaluations

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