A novel bionic algorithm inspired by plant root foraging behaviors

被引:30
|
作者
Ma, Lianbo [1 ,2 ]
Zhu, Yunlong [1 ,2 ]
Liu, Yang [3 ]
Tian, Liwei [3 ]
Chen, Hanning [4 ]
机构
[1] Chinese Acad Sci, Shenyang Inst Automat, Shenyang 110016, Peoples R China
[2] Key Lab Networked Control Syst CAS, Shenyang 110016, Peoples R China
[3] Shenyang Univ, Shenyang 110044, Peoples R China
[4] Tianjin Polytech Univ, Sch Comp Sci & Software, Tianjin 300387, Peoples R China
基金
中国国家自然科学基金;
关键词
Artificial root foraging optimizer; Bionic optimization; Root growth; Benchmark test; COLONY OPTIMIZATION; GROWTH; EVOLUTIONARY; MODEL; ARCHITECTURE;
D O I
10.1016/j.asoc.2015.08.014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this contribution, a novel bionic algorithm inspired by plant root foraging behaviors, namely artificial root foraging optimization (ARFO) algorithm, is designed and developed. The incentive mechanism of ARFO is to mimic the adaptation and randomness of plant root foraging behaviors, e.g., branching, regrowing and tropisms. A mathematical architecture is firstly designed to model the plant root foraging pattern. Under this architecture, the effects of the tropism and the self-adaptive growth behaviors are investigated. Afterward, the arithmetic realization of ARFO derived from this framework is presented in detail. In order to demonstrate the optimization performance, the proposed ARFO is benchmarked against several state-of-the-art reference algorithms on a suit of CEC 2013 and CEC 2014 functions. Computational results show a high performance of the proposed ARFO for searching a global optimum on several benchmarks, which indicates that ARFO has potential to deal with complex optimization problems. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:95 / 113
页数:19
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