Nature-Inspired Algorithms from Oceans to Space: A Comprehensive Review of Heuristic and Meta-Heuristic Optimization Algorithms and Their Potential Applications in Drones

被引:30
作者
Darvishpoor, Shahin [1 ]
Darvishpour, Amirsalar [2 ]
Escarcega, Mario [3 ]
Hassanalian, Mostafa [3 ]
机构
[1] KN Toosi Univ Technol, Dept Aerosp Engn, Tehran 1656983911, Iran
[2] Univ Tehran, Dept Comp Engn, Tehran 1417935840, Iran
[3] New Mexico Inst Min & Technol, Dept Mech Engn, Socorro, NM 87801 USA
关键词
bio-inspired; drones; heuristics; meta-heuristics; nature-inspired; optimization; NUMERICAL FUNCTION OPTIMIZATION; CHEMICAL-REACTION OPTIMIZATION; SWARM INTELLIGENCE ALGORITHM; FLOWER POLLINATION ALGORITHM; POPULATION-BASED ALGORITHM; HARMONY SEARCH ALGORITHM; FRUIT-FLY OPTIMIZATION; GLOBAL OPTIMIZATION; METAHEURISTIC ALGORITHM; DIFFERENTIAL EVOLUTION;
D O I
10.3390/drones7070427
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
This paper reviews a majority of the nature-inspired algorithms, including heuristic and meta-heuristic bio-inspired and non-bio-inspired algorithms, focusing on their source of inspiration and studying their potential applications in drones. About 350 algorithms have been studied, and a comprehensive classification is introduced based on the sources of inspiration, including bio-based, ecosystem-based, social-based, physics-based, chemistry-based, mathematics-based, music-based, sport-based, and hybrid algorithms. The performance of 21 selected algorithms considering calculation time, max iterations, error, and the cost function is compared by solving 10 different benchmark functions from different types. A review of the applications of nature-inspired algorithms in aerospace engineering is provided, which illustrates a general view of optimization problems in drones that are currently used and potential algorithms to solve them.
引用
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页数:134
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