Flood algorithm: a novel metaheuristic algorithm for optimization problems

Metaheuristic algorithms are an important area of research that provides significant advances in solving complex optimization problems within acceptable time periods. Since the performances of these algorithms vary for different types of problems, many studies have been and need to be done to propose different metaheuristic algorithms. In this article, a new metaheuristic algorithm called flood algorithm (FA) is proposed for optimization problems. It is inspired by the flow of flood water on the earth's surface. The proposed algorithm is tested both on benchmark functions and on a real-world problem of preparing an exam seating plan, and the results are compared with different metaheuristic algorithms. The comparison results show that the proposed algorithm has competitive performance with other metaheuristic algorithms used in the comparison in terms of solution accuracy and time.

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Publication Details

Journal
PeerJ Computer Science
Published
2024-10-02
DOI
https://doi.org/10.7717/peerj-cs.2278
Citations
9
Primary Topic
Metaheuristic Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
3.13
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article

Flood algorithm: a novel metaheuristic algorithm for optimization problems

Ramazan Özkan, Rüya Şamlı
9 citations
PeerJ Computer Science
Metaheuristic Optimization Algorithms Research
3.13
article

Flood algorithm: a novel metaheuristic algorithm for optimization problems

Ramazan Özkan, Rüya Şamlı
article en
9 citations

Abstract

Metaheuristic algorithms are an important area of research that provides significant advances in solving complex optimization problems within acceptable time periods. Since the performances of these algorithms vary for different types of problems, many studies have been and need to be done to propose different metaheuristic algorithms. In this article, a new metaheuristic algorithm called flood algorithm (FA) is proposed for optimization problems. It is inspired by the flow of flood water on the earth's surface. The proposed algorithm is tested both on benchmark functions and on a real-world problem of preparing an exam seating plan, and the results are compared with different metaheuristic algorithms. The comparison results show that the proposed algorithm has competitive performance with other metaheuristic algorithms used in the comparison in terms of solution accuracy and time.

PeerJ Computer ScienceVol. 10
Milli Savunma Üniversitesi (TR), Istanbul University-Cerrahpaşa (TR)
Openalex Percentile: Top 7%
Metaheuristic Optimization Algorithms Research
3.13
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Flood algorithm: a novel metaheuristic algorithm for optimization problems — Ramazan Özkan, Rüya Şamlı · PeerJ Computer Science (2024) | TGRS Research Map | TGRS