A Comparative Study of Common Nature-Inspired Algorithms for Continuous Function Optimization

Over previous decades, many nature-inspired optimization algorithms (NIOAs) have been proposed and applied due to their importance and significance. Some survey studies have also been made to investigate NIOAs and their variants and applications. However, these comparative studies mainly focus on on...

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Bibliographic Details
Published in:Entropy (Basel, Switzerland) Vol. 23; no. 7; p. 874
Main Authors: Wang, Zhenwu, Qin, Chao, Wan, Benting, Song, William Wei
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 08.07.2021
MDPI
Subjects:
Algorithms
bio-inspired algorithm
black-box optimization benchmarking
Comparative studies
Continuity (mathematics)
Genetic algorithms
Heuristic
Heuristic methods
Intelligence
meta-heuristic algorithm
nature-inspired algorithm
Optimization
Optimization algorithms
Parameter sensitivity
Review
Stability analysis
statistical test
swarm intelligence algorithm
nature-inspired algorithm
meta-heuristic algorithm
statistical test
black-box optimization benchmarking
swarm intelligence algorithm
bio-inspired algorithm
ISSN:1099-4300, 1099-4300
Online Access:Get full text
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Summary:Over previous decades, many nature-inspired optimization algorithms (NIOAs) have been proposed and applied due to their importance and significance. Some survey studies have also been made to investigate NIOAs and their variants and applications. However, these comparative studies mainly focus on one single NIOA, and there lacks a comprehensive comparative and contrastive study of the existing NIOAs. To fill this gap, we spent a great effort to conduct this comprehensive survey. In this survey, more than 120 meta-heuristic algorithms have been collected and, among them, the most popular and common 11 NIOAs are selected. Their accuracy, stability, efficiency and parameter sensitivity are evaluated based on the 30 black-box optimization benchmarking (BBOB) functions. Furthermore, we apply the Friedman test and Nemenyi test to analyze the performance of the compared NIOAs. In this survey, we provide a unified formal description of the 11 NIOAs in order to compare their similarities and differences in depth and a systematic summarization of the challenging problems and research directions for the whole NIOAs field. This comparative study attempts to provide a broader perspective and meaningful enlightenment to understand NIOAs.
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ISSN:1099-4300
1099-4300
DOI:10.3390/e23070874