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Special Issue: Harmonizing Theory with Practice in Swarm and Evolutionary Computation

Guest Editor

Prof. Yong-Hyuk Kim
School of Software, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 01897, Republic of Korea
Email: yhdfly@kw.ac.kr

Manuscript Topics


Swarm and Evolutionary Computation (SEC) stands as a vast and burgeoning domain within contemporary computer sciences, encompassing nature-inspired systems capable of exhibiting intelligent behavior. This capability allows them to optimize a wide array of complex real-world scenarios that defy resolution through the direct application of purely theoretical exact approaches.


Historically, the swarm intelligence and evolutionary computation communities operated independently, despite sharing common objectives. Over time, both fields evolved separately. Presently, advancements in these areas have given rise to highly hybrid, interconnected, and self-adaptive frameworks, incorporating ideas from both domains. This necessitates increased collaboration and joint efforts among SEC researchers and practitioners in related fields such as engineering, robotics, and so on.


SEC research proves highly relevant across various real-world domains, ranging from engineering to finance. It finds application in scenarios where optimization is essential for making intelligent decisions or minimizing/maximizing costs/profits.


Notably, SEC systems play a pivotal role in other realms of computer science, such as Machine Learning (ML) and Deep Learning (DL). Hybrid methods leverage SEC algorithms to optimize, train, or design ML and DL systems. Conversely, ML methods enhance the efficiency of non-conforming SEC, addressing issues like premature convergence, lack of selection pressure, or difficulties in maintaining adequate population diversity.


Regardless of the problem's nature—be it single or multi-objective, dynamic or static, continuous or discrete—this Special Issue aims to compile articles showcasing the latest developments within the SEC community. These include successful real-world applications and cutting-edge algorithmic designs. Submissions investigating the algorithmic behavior and dynamics of SEC methods are also encouraged.


Topics of Interest:
• Mathematical or geometric considerations related to search space and fitness landscape.
• Integration of computational intelligence in optimization utilizing SEC principles.
• Machine learning with an evolutionary approach.
• Evolutionary approaches in neural networks.
• Modeling through surrogates.
• Application of operations research in SEC systems.
• Utilizing SEC algorithms for forecasting and data mining.
• Practical applications in the real world such as scheduling or deploying issues, financial engineering, etc.


Instruction for Authors
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Please submit your manuscript to online submission system
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Paper Submission

All manuscripts will be peer-reviewed before their acceptance for publication. The deadline for manuscript submission is 28 February 2025

Published Papers(7)

Editorial
Special Issue "Harmonizing Theory with Practice in Swarm and Evolutionary Computation"
Yong-Hyuk Kim
2025, Volume 10, Issue 6: 13692-13694. doi: 10.3934/math.2025616
Abstract HTML PDF Viewed (193)
Research article
An adaptive greedy repair operator in a genetic algorithm for the minimum vertex cover problem
Seung-Hyun Moon Yourim Yoon
2025, Volume 10, Issue 6: 13365-13392. doi: 10.3934/math.2025600
Abstract HTML PDF Cited (1) Viewed (240)
Research article
An efficient eigenvector-based crossover for differential evolution: Simplifying with rank-one updates
Tae Jong Choi
2025, Volume 10, Issue 2: 3500-3522. doi: 10.3934/math.2025162
Abstract HTML PDF Cited (1) Viewed (621)
Research article
Enhancing sewage flow prediction using an integrated improved SSA-CNN-Transformer-BiLSTM model
Jiawen Ye Lei Dai Haiying Wang
2024, Volume 9, Issue 10: 26916-26950. doi: 10.3934/math.20241310
Abstract HTML PDF Cited (2) Viewed (1799)
Research article
Improving modularity score of community detection using memetic algorithms
Dongwon Lee Jingeun Kim Yourim Yoon
2024, Volume 9, Issue 8: 20516-20538. doi: 10.3934/math.2024997
Abstract HTML PDF Cited (2) Viewed (1627)
Research article
MSFSS: A whale optimization-based multiple sampling feature selection stacking ensemble algorithm for classifying imbalanced data
Shuxiang Wang Changbin Shao Sen Xu Xibei Yang Hualong Yu
2024, Volume 9, Issue 7: 17504-17530. doi: 10.3934/math.2024851
Abstract HTML PDF Cited (2) Viewed (1407)
Research article
An optimal power flow solution for a power system integrated with renewable generation
Hisham Alghamdi Lyu-Guang Hua Muhammad Riaz Ghulam Hafeez Safeer Ullah Monji Mohamed Zaidi Mohammed Jalalah
2024, Volume 9, Issue 3: 6603-6627. doi: 10.3934/math.2024322
Abstract HTML PDF Cited (9) Viewed (1974)