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Evo-Panel: Dynamic Visualization Tool for Optimization Process

Published: 01 August 2024 Publication History

Abstract

This article for the Hot-off-the-Press track at GECCO 2024 summarizes recent work titled 'Evo-Panel: Dynamic Visualization Tool for Optimization Process', published in IEEE Transactions on Emerging Topics in Computational Intelligence [4]. We believe this work is of interest to the GECCO community as it represents the first attempt to establish a comprehensive dynamic visualization tool, Evo-Panel, capable of directly and flexibly illustrating the detailed procedures of metaheuristics and optimization methods in solving numerical benchmark functions. The objective of Evo-Panel is to help users identify the influence of the design formulas, operations, and parameters on the capabilities and performances of the algorithms. Using Evo-Panel, users can trace each movement, intuitively observe the process, and interpret the processes related to evolutionary algorithms (EAs), which are important to explainable AI. Moreover, Evo-Panel can perform a comparative analysis to illustrate the differences between algorithms. The case study results demonstrate that employing Evo-Panel enables professors to explain optimization algorithms visually engagingly and enhances the students' understanding of EAs. The tool can promote CI-related education from teaching and learning perspectives. Furthermore, researchers can use it to obtain information for analysis, facilitate debugging, verify design ideas, gain insights into the process, and improve the design of EAs.

References

[1]
Yao-Hsin Chou, Shu-Yu Kuo, Li-Sheng Yang, and Chia-Yun Yang. 2018. Next Generation Metaheuristic: Jaguar Algorithm. IEEE Access 6 (2018), 9975--9990.
[2]
Yao-Hsin Chou, Ching-Hsuan Wu, Yu-Chi Jiang, Shu-Yu Kuo, and Sy-Yen Kuo. 2024. Nanoscale Precision-Related Challenges in Classical and Quantum Optimization. IEEE Nanotechnology Magazine (2024), 1--13.
[3]
J. Kennedy and R. Eberhart. 1995. Particle Swarm Optimization. In Proceedings of ICNN'95 - International Conference on Neural Networks, Vol. 4. 1942--1948.
[4]
Shu-Yu Kuo, Yu-Chi Jiang, Cheng-Yen Hua, Yao-Hsin Chou, and Sy-Yen Kuo. 2023. Evo-Panel: Dynamic Visualization Tool for Optimization Process. IEEE Transactions on Emerging Topics in Computational Intelligence 7, 6 (2023), 1717--1732.
[5]
Shu-Yu Kuo, Ching-Hsuan Wu, Cheng-Chun Chen, and Yao-Hsin Chou. 2021. A Novel Metaheuristic: Fast Jaguar Algorithm. In 2021 IEEE International Conference on Systems, Man, and Cybernetics. 146--151.
[6]
Seyedali Mirjalili and Andrew Lewis. 2016. The Whale Optimization Algorithm. Advances in Engineering Software 95 (2016), 51--67.

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cover image ACM Conferences
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference Companion
July 2024
2187 pages
ISBN:9798400704956
DOI:10.1145/3638530
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 third-party components of this work must be honored. For all other uses, contact the owner/author(s).

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Association for Computing Machinery

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Publication History

Published: 01 August 2024

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Author Tags

  1. computational intelligence
  2. evolutionary computation
  3. interactive systems
  4. metaheuristics
  5. optimization visualization tools
  6. XAI

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  • National Science and Technology Council (Taiwan)
  • National Center for Theoretical Sciences

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GECCO '24 Companion
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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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