A Bio-Inspired Method for Engineering Design Optimization Inspired by Dingoes Hunting Strategies

被引:103
作者
Peraza-Vazquez, Hernan [1 ]
Pena-Delgado, Adrian F. [2 ]
Echavarria-Castillo, Gustavo [1 ]
Beatriz Morales-Cepeda, Ana [3 ]
Velasco-Alvarez, Jonas [4 ]
Ruiz-Perez, Fernando [1 ]
机构
[1] Inst Politecn Nacl, CICATA Altamira, Km 14-5 Carretera Tampico Puerto Ind Altamira, Altamira 89600, Tamaulipas, Mexico
[2] Univ Tecnol Altamira, Puerto Ind Altamira, Blvd Rios Km 3 100, Altamira 89601, Tamaulipas, Mexico
[3] TecNM Inst Tecnol Ciudad Madero, Juventino Rosas y Jesus Urueta S-N, Madero 89318, Tamaulipas, Mexico
[4] CONACyT, Ctr Invest Matemat CIMAT AC, Bartolome Casas 314, Guanajuato 20259, Mexico
关键词
ALGORITHM; EVOLUTION; VARIANTS;
D O I
10.1155/2021/9107547
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A novel bio-inspired algorithm, namely, Dingo Optimization Algorithm (DOA), is proposed for solving optimization problems. The DOA mimics the social behavior of the Australian dingo dog. The algorithm is inspired by the hunting strategies of dingoes which are attacking by persecution, grouping tactics, and scavenging behavior. In order to increment the overall efficiency and performance of this method, three search strategies associated with four rules were formulated in the DOA. These strategies and rules provide a fine balance between intensification (exploitation) and diversification (exploration) over the search space. The proposed method is verified using several benchmark problems commonly used in the optimization field, classical design engineering problems, and optimal tuning of a Proportional-Integral-Derivative (PID) controller are also presented. Furthermore, the DOA's performance is tested against five popular evolutionary algorithms. The results have shown that the DOA is highly competitive with other metaheuristics, beating them at the majority of the test functions.
引用
收藏
页数:19
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