An Urban Pigeon-Inspired Optimiser for Unconstrained Continuous Domains

Blanco, Angie L.; Chaparro, Nathalia; Rojas–Galeano, Sergio

doi:10.1109/bracis.2019.00097

Cited by 6 publications

(2 citation statements)

References 18 publications

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“…Hoopoe heuristic optimization (HHO) is another bird-inspired algorithm developed by El-Dosuky et al [158]. Urban pigeon-inspired optimizer (UPIO) was developed based on the foraging behavior of groups of urban pigeons [159]. Another algorithm based on bat's echolocation capabilities is called the bat sonar optimization algorithm (BSOA) [160].…”

Section: Other Algorithmsmentioning

confidence: 99%

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

Darvishpoor,

Darvishpour,

Escarcega

et al. 2023

Drones

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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.

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Section: Other Algorithmsmentioning

confidence: 99%

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

Darvishpoor,

Darvishpour,

Escarcega

et al. 2023

Drones

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“…Binary fish migration optimization algorithm (ABFMO) [ 24 ] and improved binary symbiotic organism search algorithm (IBSOS) using transfer function also solved the FS problem [ 25 ]. Accordingly, the pigeon flock optimization algorithm (PIO) and the gray wolf optimization algorithm (GWO) were improved for better application in feature selection [ 26 , 27 , 28 ]. The pigeon flock optimization algorithm simulates the pigeons’ homing behavior.…”

Section: Introductionmentioning

confidence: 99%

Improved Binary Grasshopper Optimization Algorithm for Feature Selection Problem

Wang

Chu

Tian

et al. 2022

Entropy

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The migration and predation of grasshoppers inspire the grasshopper optimization algorithm (GOA). It can be applied to practical problems. The binary grasshopper optimization algorithm (BGOA) is used for binary problems. To improve the algorithm’s exploration capability and the solution’s quality, this paper modifies the step size in BGOA. The step size is expanded and three new transfer functions are proposed based on the improvement. To demonstrate the availability of the algorithm, a comparative experiment with BGOA, particle swarm optimization (PSO), and binary gray wolf optimizer (BGWO) is conducted. The improved algorithm is tested on 23 benchmark test functions. Wilcoxon rank-sum and Friedman tests are used to verify the algorithm’s validity. The results indicate that the optimized algorithm is significantly more excellent than others in most functions. In the aspect of the application, this paper selects 23 datasets of UCI for feature selection implementation. The improved algorithm yields higher accuracy and fewer features.

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Binary Optimisation with an Urban Pigeon-Inspired Swarm Algorithm

Rojas–Galeano

2019

Communications in Computer and Information Science

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An Urban Pigeon-Inspired Optimiser for Unconstrained Continuous Domains

Cited by 6 publications

References 18 publications

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

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

Improved Binary Grasshopper Optimization Algorithm for Feature Selection Problem

Binary Optimisation with an Urban Pigeon-Inspired Swarm Algorithm

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