An Artificial Bee Colony Algorithm Guided by Lévy Flights Disturbance Strategy for Global Optimization

Ma, Wei; Sun, Zhengxing; Li, Junlou; Song, Mofei; Lang, Xufeng; Cheng, Liang

doi:10.1007/978-3-319-13707-0_54

Cited by 4 publications

(5 citation statements)

References 13 publications

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“…In the basic ABC algorithm, the scout bee uses (11) to replace the exhausted solution with a new one. Therefore, exhausted solutions are replaced by entirely random ones that neglect the information gained by the algorithm as the search progresses.…”

Section: Improved Equation For the Scout Beementioning

confidence: 99%

“…The scaling parameter 𝜙 in Equation (18) has been fixed to 0.001 in [10] and 0.01 in [11], but fixing the value of 𝜙 to 0.1 has led to better statistical results with the GFABC-LF. Figure 10 depicts the average cost and standard deviation values corresponding to the values of 0.001, 0.01, 0.1, and 1 for 𝜙.…”

Section: Sensitivity Analysis and Parameters Tuningmentioning

confidence: 99%

“…Otherwise, the counter is incremented by one. In each iteration, if the maximum counter value in the population exceeded a certain predefined value, known as the limit, the scout bee is applied to replace the associated solution with a randomly generated one using (11).…”

Section: Abc Algorithmmentioning

confidence: 99%

“…The purpose of this case study is to demonstrate the effect of each proposed improvement to the ABC algorithm. The proposed algorithm is compared with the basic ABC algorithm, GFABC −1 , which designates the proposed algorithm without Levy flights and with (11) instead of (20), and GFABC which expresses the proposed algorithm without Levy flights. Approximately, the same TOFE value is used by all the algorithms.…”

Section: Case Study 1 (Validation Of the Proposed Improvements)mentioning

confidence: 99%

“…On the other hand, the Levy flights which mimic the flight behaviour of many insects and animals have been proposed to improve the performance of several stochastic algorithms by enhancing their capability for escaping from local minimums [7][8][9]. To improve the performance for variants of the ABC algorithm, these variants have been augmented with the Levy flights in [10][11][12]. On the other hand, it is known that the ABC algorithm has good exploration and poor exploitation capabilities [13,14].…”

Section: Introductionmentioning

confidence: 99%

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Deterministic‐like solution to the non‐convex economic dispatch problem

El-Sayed

El-Saadany

Zeineldin

et al. 2020

IET Generation Trans & Dist

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This paper proposes a novel stochastic solution method for the static nonconvex power economic dispatch problem. All practical features such as valve point effects, ramp rate limits, prohibited operating zones, multiple fuel options, spinning reserve constraints, and transmission losses are considered. To develop the proposed algorithm, two modifications that significantly enhance the exploitation capability of the artificial bee colony algorithm are introduced. The first modification concerns onlooker and employed bees to focus their search around the best solution found so far. The second modification optimizes the escaping behavior from local minimums using scout bees. The proposed modifications form a multi-level concentric search around the best solution found. Finally, combining the modified artificial bee colony algorithm with Levy flight cycles, which improve the escaping capability from local minimums, leads to the proposed algorithm. The algorithm parameters have been tuned to provide a deterministic-like solution with ten benchmark problems. The improvement added by each proposed modification to the artificial bee colony algorithm has been confirmed using the Wilcoxon rank-sum test. The obtained results by the proposed algorithm are superior compared to those reported in the literature. Moreover, estimated probabilities of more than 99.9% to obtain the global optimal solution are achieved. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Improved Equation For the Scout Beementioning

confidence: 99%