Flower pollination algorithm: a comprehensive review

Mohamed Abdel-Basset; Laila A. Shawky

doi:10.1007/s10462-018-9624-4

Flower pollination algorithm: a comprehensive review

Mohamed Abdel-Basset
, Laila A. Shawky

Research output: Contribution to journal › Review article › peer-review

203 Citations (Scopus)

Abstract

Flower pollination algorithm (FPA) is a computational intelligence metaheuristic that takes its metaphor from flowers proliferation role in plants. This paper provides a comprehensive review of all issues related to FPA: biological inspiration, fundamentals, previous studies and comparisons, implementation, variants, hybrids, and applications. Besides, it makes a comparison between FPA and six different metaheuristics such as genetic algorithm, cuckoo search, grasshopper optimization algorithm, and others on solving a constrained engineering optimization problem. The experimental results are statistically analyzed with non-parametric Friedman test which indicates that FPA is superior more than other competitors in solving the given problem.

Original language	English
Pages (from-to)	2533-2557
Number of pages	25
Journal	Artificial Intelligence Review
Volume	52
Issue number	4
DOIs	https://doi.org/10.1007/s10462-018-9624-4
Publication status	Published - 1 Dec 2019
Externally published	Yes

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title = "Flower pollination algorithm: a comprehensive review",

abstract = "Flower pollination algorithm (FPA) is a computational intelligence metaheuristic that takes its metaphor from flowers proliferation role in plants. This paper provides a comprehensive review of all issues related to FPA: biological inspiration, fundamentals, previous studies and comparisons, implementation, variants, hybrids, and applications. Besides, it makes a comparison between FPA and six different metaheuristics such as genetic algorithm, cuckoo search, grasshopper optimization algorithm, and others on solving a constrained engineering optimization problem. The experimental results are statistically analyzed with non-parametric Friedman test which indicates that FPA is superior more than other competitors in solving the given problem.",

keywords = "Cuckoo search, Flower pollination algorithm, Genetic algorithm, Metaheuristic, Optimization",

author = "Mohamed Abdel-Basset and Shawky, \{Laila A.\}",

note = "Publisher Copyright: {\textcopyright} 2018, Springer Science+Business Media B.V., part of Springer Nature.",

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T1 - Flower pollination algorithm

T2 - a comprehensive review

AU - Abdel-Basset, Mohamed

AU - Shawky, Laila A.

PY - 2019/12/1

Y1 - 2019/12/1

N2 - Flower pollination algorithm (FPA) is a computational intelligence metaheuristic that takes its metaphor from flowers proliferation role in plants. This paper provides a comprehensive review of all issues related to FPA: biological inspiration, fundamentals, previous studies and comparisons, implementation, variants, hybrids, and applications. Besides, it makes a comparison between FPA and six different metaheuristics such as genetic algorithm, cuckoo search, grasshopper optimization algorithm, and others on solving a constrained engineering optimization problem. The experimental results are statistically analyzed with non-parametric Friedman test which indicates that FPA is superior more than other competitors in solving the given problem.

AB - Flower pollination algorithm (FPA) is a computational intelligence metaheuristic that takes its metaphor from flowers proliferation role in plants. This paper provides a comprehensive review of all issues related to FPA: biological inspiration, fundamentals, previous studies and comparisons, implementation, variants, hybrids, and applications. Besides, it makes a comparison between FPA and six different metaheuristics such as genetic algorithm, cuckoo search, grasshopper optimization algorithm, and others on solving a constrained engineering optimization problem. The experimental results are statistically analyzed with non-parametric Friedman test which indicates that FPA is superior more than other competitors in solving the given problem.

KW - Cuckoo search

KW - Flower pollination algorithm

KW - Genetic algorithm

KW - Metaheuristic

KW - Optimization

UR - https://www.scopus.com/pages/publications/85043703779

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M3 - Review article

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VL - 52

SP - 2533

EP - 2557

JO - Artificial Intelligence Review

JF - Artificial Intelligence Review

IS - 4

ER -

Flower pollination algorithm: a comprehensive review

Abstract

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