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Fractional-order artificial bee colony algorithm with application in robot path planning
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AI
DOI：10.1016/j.ejor.2022.11.007.png)
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Abstract
En 中文
Artificial bee colony (ABC) algorithm is a popular meta-heuristic optimization algorithm inspired by the foraging behaviors of honeybees. Although ABC has outstanding exploration ability, it has certain weak-ness like poor exploitation capability and low solution precision. Therefore, to tackle these weakness and improve the performance, an ABC algorithm based on fractional-order calculus (FOABC) is proposed. More specially, the memory properties of fractional-order calculus is incorporated into onlooker bee phase to improve the local-search capability. Each time generating a new candidate solution, the previous foraging behaviors stored in memory are referred. Another enhanced search strategy is adopted in employed bee phase to avoid losing the balance between diversification and intensification. To evaluate the performance of FOABC, several groups of experiments are conducted on CEC 2017 benchmark problems. According to the experimental studies, FOABC is outstanding in comparisons with ABC variants and also performs re-markably well in practical applications, namely robot path planning.(c) 2022 Elsevier B.V. All rights reserved.
Keywords:
Global optimization
Artificial bee colony algorithm
Fractional calculus
L?vy distribution
Robot path planning
Journal
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6
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2.2W
Citations:
6.4W