research-article

Survey of Swarm Intelligence Algorithms

Authors:

Suganya Selvaraj,

Eunmi ChoiAuthors Info & Claims

ICSIM '20: Proceedings of the 3rd International Conference on Software Engineering and Information Management

Pages 69 - 73

https://doi.org/10.1145/3378936.3378977

Published: 07 March 2020 Publication History

Abstract

Swarm Intelligence (SI) is an AI technique that has the collective behavior of a decentralized, self-organized system. SI has more advantages such as scalability, adaptability, collective robustness and individual simplicity and also has the ability to solve complex problems. Besides, SI algorithms also have few issues in time-critical applications, parameter tuning, and stagnation. SI algorithms need to be studied more to overcome these kinds of issues. In this paper, we studied a few popular algorithms in detail to identify important control parameters and randomized distribution. We also studied and summarized the performance comparison of SI algorithms in different applications.

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Cited By

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Alsaidi AAl-Sorori WMohsen A(2024)DNCCLA: Discrete New Caledonian Crow Learning Algorithm for Solving Traveling Salesman ProblemApplied Computational Intelligence and Soft Computing10.1155/acis/53249982024:1Online publication date: 17-Dec-2024
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ICSIM '20: Proceedings of the 3rd International Conference on Software Engineering and Information Management

January 2020

258 pages

ISBN:9781450376907

DOI:10.1145/3378936

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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University of Science and Technology of China: University of Science and Technology of China

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Association for Computing Machinery

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Publication History

Published: 07 March 2020

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the Ministry of Education BK21 program, Korea

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ICSIM '20

ICSIM '20: The 3rd International Conference on Software Engineering and Information Management

January 12 - 15, 2020

NSW, Sydney, Australia

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Cited By

Nguyen L(2024)Swarm Intelligence-Based Multi-Robotics: A Comprehensive ReviewAppliedMath10.3390/appliedmath40400644:4(1192-1210)Online publication date: 2-Oct-2024
https://doi.org/10.3390/appliedmath4040064
Alsaidi AAl-Sorori WMohsen A(2024)DNCCLA: Discrete New Caledonian Crow Learning Algorithm for Solving Traveling Salesman ProblemApplied Computational Intelligence and Soft Computing10.1155/acis/53249982024:1Online publication date: 17-Dec-2024
https://doi.org/10.1155/acis/5324998
Riku KMatsushima K(2024)Solving PnP Problem Using Improved Sparrow Search Algorithm2024 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)10.1109/ISPACS62486.2024.10868791(1-4)Online publication date: 10-Dec-2024
https://doi.org/10.1109/ISPACS62486.2024.10868791
Ghamari SHajihosseini MHabibi DAziz A(2024)Design of an Adaptive Robust PI Controller for DC/DC Boost Converter Using Reinforcement-Learning Technique and Snake Optimization AlgorithmIEEE Access10.1109/ACCESS.2024.344058012(141814-141829)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3440580
WANG CZHANG SMA TXIAO YCHEN MWANG L(2024)Swarm intelligence: A survey of model classification and applicationsChinese Journal of Aeronautics10.1016/j.cja.2024.03.019(102982)Online publication date: Mar-2024
https://doi.org/10.1016/j.cja.2024.03.019
Chen KXiao BWang CLiu XLiang SZhang X(2023)Cuckoo Coupled Improved Grey Wolf Algorithm for PID Parameter TuningApplied Sciences10.3390/app13231294413:23(12944)Online publication date: 4-Dec-2023
https://doi.org/10.3390/app132312944
Selvaraj SChoi E(2022)Dynamic Sub-Swarm Approach of PSO Algorithms for Text Document ClusteringSensors10.3390/s2224965322:24(9653)Online publication date: 9-Dec-2022
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Bangyal WNisar KSoomro TAg Ibrahim AMallah GHassan NRehman N(2022)An Improved Particle Swarm Optimization Algorithm for Data ClassificationApplied Sciences10.3390/app1301028313:1(283)Online publication date: 26-Dec-2022
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Emambocus BJasser MAmphawan A(2022)An Optimized Continuous Dragonfly Algorithm Using Hill Climbing Local Search to Tackle the Low Exploitation ProblemIEEE Access10.1109/ACCESS.2022.320475210(95030-95045)Online publication date: 2022
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Anand AYukta PArihant SNivi U(2022)Swarm Intelligence Using Collision Avoidance SystemSoft Computing: Theories and Applications10.1007/978-981-19-0707-4_29(307-317)Online publication date: 2-Jun-2022
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