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Dual-Search Artificial Bee Colony Algorithm for Engineering Optimization
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DOI：10.1109/ACCESS.2019.2899743.png)
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Abstract
En 中文
With the development of science and technology, the accuracy requirements for solving engineering problems are getting stricter than before. Most structural design optimization problems in civil and mechanical engineering have proven to be the non-deterministic polynomial hard problems. The artificial bee colony (ABC) algorithm has been proven to be an effective method of design optimization problems. This paper proposes an improved ABC algorithm (DSM-ABC) combined with dual-search mechanism containing Levy flight and differential self-perturbation and applies it to three classical structural design problems, including cantilever beam design, gear train design, and three-bar truss design. The experimental results of benchmark functions from CEC2005 reveal that the proposed DSM-ABC algorithm accelerates the convergence and improves the performance. Eventually, the obtained results of optimization structural design problems prove that the DSM-ABC algorithm has a strong superiority compared with the state-ofthe-art algorithms in solving optimization engineering design problems.
Keywords:
Artificial bee colony algorithm
dual search mechanism
Levy flight
differential self-disturbance mechanism
engineering optimization
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