Improved dolphin swarm optimization algorithm based on information entropy

• Autorzy: Li Y. , Wang X.

Identyfikatory

DOI

10.24425/bpasts.2019.130177

• Języki publikacji: EN

Abstrakty

EN

In order to overcome the shortcomings of the dolphin algorithm, which is prone to falling into local optimum and premature conver-gence, an improved dolphin swarm algorithm, based on the standard dolphin algorithm, was proposed. As a measure of uncertainty, information entropy was used to measure the search stage in the dolphin swarm algorithm. Adaptive step size parameters and dynamic balance factors were introduced to correlate the search step size with the number of iterations and fitness, and to perform adaptive adjustment of the algorithm. Simulation experiments show that, comparing with the basic algorithm and other algorithms, the improved dolphin swarm algorithm is feasible and effective.

Słowa kluczowe

EN

dolphin swarm optimization; information entropy; convergence; self-adaptive; combinational optimization

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2019
• Tom: Vol. 67, nr 4
• Strony: 679--685
• Opis fizyczny: Bibliogr. 24 poz., rys., tab.

Twórcy

autor

Li Y.

• Hebei University of Engineering, Handan056038, China

autor

Wang X.

• Hebei University of Engineering, Handan056038, China

Bibliografia

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Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).