Surrogate-Assisted Hybrid Meta-Heuristic Algorithm with an Add-Point Strategy for a Wireless Sensor Network

. 2023 Feb 9;25(2):317. doi: 10.3390/e25020317

Algorithm 4 Add-point strategy based on historical surrogate model information.

1:
Historical surrogate model information has been saved in SADB
2:
Obtain the best individual in the current population (best), the mean of the top tpc individuals (mean), and the random individual in the top third (rand).
3:
The fitness values of the optimal individual, the mean individual and the random individual were calculated using the new RBF surrogate model $R B F_N E W$ and the historical RBF surrogate model $R B F_O L D$ , respectively.
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if $R B F_N E W (b e s t) < R B F_O L D (b e s t)$ then
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Then the best individual and its true fitness value are saved to the SDB.
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end if
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if $R B F_N E W (m e a n) < R B F_O L D (m e a n)$ then
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Save the mean individual and its true fitness value to SDB.
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end if
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if Both the best individual and the mean individual were not added to the SDB then
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Then the rand individual and its true fitness values are saved to the SDB.
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end if