Help ?

IGMIN: あなたがここにいてくれて嬉しいです. お願いクリック '新しいクエリを作成してください' 当ウェブサイトへの初めてのご訪問で、さらに情報が必要な場合は.

すでに私たちのネットワークのメンバーで、すでに提出した質問に関する進展を追跡する必要がある場合は, クリック '私のクエリに連れて行ってください.'

Browse by Subjects

Welcome to IgMin Research – an Open Access journal uniting Biology, Medicine, and Engineering. We’re dedicated to advancing global knowledge and fostering collaboration across scientific fields.

Members

Our mission is to create an environment where different scientific fields can come together to fuel progress.

Articles

Our mission is to create an environment where different scientific fields can come together to fuel progress.

Explore Content

Our mission is to create an environment where different scientific fields can come together to fuel progress.

Identify Us

Our mission is to create an environment where different scientific fields can come together to fuel progress.

IgMin Corporation

Welcome to IgMin, a leading platform dedicated to enhancing knowledge dissemination and professional growth across multiple fields of science, technology, and the humanities. We believe in the power of open access, collaboration, and innovation. Our goal is to provide individuals and organizations with the tools they need to succeed in the global knowledge economy.

Publications Support
[email protected]
E-Books Support
[email protected]
Webinars & Conferences Support
[email protected]
Content Writing Support
[email protected]
IT Support
[email protected]

Search

Explore Section

Content for the explore section slider goes here.

60 of 165
Contribution to the Knowledge of Ground Beetles (Coleoptera: Carabidae) from Pakistan
Zubair Ahmed, Haseeb Ahmed Lalika, Imran Khatri and Eric Kirschenhofer
62 of 165
Investigation of Lateral Vibrations in Turbine-generator Unit 5 of the Inga 2 Hydroelectric Power Plant
André Mampuya Nzita, Edmond Phuku Phuati, Robert Muanda Ngimbi, Guyh Dituba Ngoma and Nathanaël Masiala Mavungu
Abstract

要約 at IgMin Research

Our mission is to create an environment where different scientific fields can come together to fuel progress.

Engineering Group Research Article 記事ID: igmin172

Improved Energy Valley Optimizer with Levy Flight for Optimization Problems

Data Engineering Artificial IntelligenceMachine Learning DOI10.61927/igmin172 Affiliation

Affiliation

    1Department of Information Systems, Al Alson Higher Institute, Cairo 11762, Egypt

    2Department of Systems and Computer Engineering, Faculty of Engineering, Alazhar University, Cairo, Egypt

865
VIEWS
299
DOWNLOADS
Connect with Us

要約

Energy Valley Optimizer (EVO) is one of the recent metaheuristic algorithms. It draws inspiration from advanced principles in physics related to particle stability and decay modes. This paper presents a new Energy Valley Optimizer (EVO) and levy flights that are hybrid to improve the EVO in solving optimization problems. Levy flight is one of the most important randomization techniques. Fifteen mathematical test functions (five unimodal functions, four multimodal functions, and six composite functions) are solved with the proposed algorithm. We also compare our results with previous results of metaheuristic algorithms. The statistical results show that the results of the Levy Energy Valley Optimizer (LEVO) outperform other algorithms in almost all mathematical test functions.

数字

参考文献

    1. Azizi M, Aickelin U, A Khorshidi H, Baghalzadeh Shishehgarkhaneh M. Energy valley optimizer: a novel metaheuristic algorithm for global and engineering optimization. Sci Rep. 2023 Jan 5;13(1):226. doi: 10.1038/s41598-022-27344-y. PMID: 36604589; PMCID: PMC9816156.
    2. Boussaïd I, Lepagnot J, and Siarry P, A survey on optimization metaheuristics. Inform Sci. 2013; 237: 82–117.
    3. Holland JH, Reitman JS. Cognitive systems based on adaptive algorithms. ACM SIGART Bull. 1977; 49–49.
    4. Colorni A, Dorigo M, Maniezzo V. Distributed optimization by ant colonies. In: Proceedings of the first European conference on artificial life. 1991; 134–42.
    5. Eberhart RC, Kennedy J. A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science. 1995; 39–43.
    6. Karaboga D, Basturk B. A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J Global Optim. 2007; 39:459–71.
    7. Rajabioun R. Cuckoo optimization algorithm. Appl Soft Comput. 2011; 11:5508–18.
    8. Yang X-S. Firefly algorithm, Levy flights and global optimization. In: Research and development in intelligent systems XXVI. Springer. 2010; 209–18.
    9. Seyedali M, Mohammad MS, Andrew L. Grey wolf optimizer. Adv Eng Software. 2014; 69:46–61.
    10. Faramarzi A, Heidarinejad M, Stephens B, Mirjalili S. Equilibrium optimizer: A novel optimization algorithm. Knowl.-Based Syst. 2020; 191:
    11. MiarNaeimi F, Azizyan G, Rashki M. ‘Horse herd optimization algorithm: A nature-inspired algorithm for high-dimensional optimization problems.’ Knowl.-Based Syst. 2021; 213: 106711.
    12. Trojovská E, Dehghani M, Leiva V. Drawer Algorithm: A New Metaheuristic Approach for Solving Optimization Problems in Engineering. Biomimetics. 2023; 8: 239.
    13. Trojovský P, Dehghani M. A new bio‑inspired metaheuristic algorithm for solving optimization problems based on walruses behavior. Scientific Reports. 2023; 13: 8775.
    14. Elmanakhly DA. An Improved Equilibrium Optimizer Algorithm for Features Selection: Methods and Analysis. IEEE Access; 9, 2021.
    15. Yilmaz S, Kucuksille E. A New Modification Approach on Bat Algorithm for Solving Optimization Problems. Applied Soft Computing Journal.
    16. Chechkin A, Gonchar V, klafter J, Metzler R. Fundomentals of Lévy Flight processes. Adv Chem Phys. 2006; 133B: 439.
    17. Fathi S, Makhlouf MAA, Osman E, Ahmed MA. An Energy-Efficient Compression Algorithm of ECG Signals in Remote Healthcare Monitoring Systems. IEEE Access. 2022; 10: 39129-39144.
    18. ELmanakhly DA. BinHOA: Efficient Binary Horse Herd Optimization Method for Feature Selection: Analysis and Validations. IEEE ACCESS. 2022; 10.
    19. Scharf I, Ovadia O. Factors influencing site abandonment and site selection in a sit-and-wait predator: a review of pit-building antlion larvae. J Insect Behav. 2006; 19:197–218.
    20. Grzimek B, Schlager N, Olendorf D, McDade MC. Grzimek’s animal life encyclopedia. Michigan: Gale Farmington Hills. 2004.
    21. Yang XS. Nature-Inspired Metaheuristic Algorithms second edition.
    22. Brown CT, Liebovitch LS, Glendon R, Lévy Flights in Dobe Ju/’hoansi Foraging Patterns. Hum Ecol. 2007; 35:129-138.
    23. Cuevas E, Echavarría A, Ramírez-Ortegón MA. An optimization algorithm inspired by the States of Matter that improves the balance between exploration and exploitation. Applied Intelligence. 2014; 40(2): 256-272.
    24. Yang XS. A new metaheuristic bat-inspired algorithm. In: Nature inspired cooperative strategies for optimization (NICSO 2010). Springer; 2010; 65–74.
    25. Yang XS. Flower pollination algorithm for global optimization. In: Unconventional computation and natural computation. 2012; 240–9.
    26. Yang XS, Deb S. Cuckoo search via Lévy flights. In: World congress on nature & biologically inspired computing. 2009. NaBIC 2009; 210–4.

類似の記事

Slip Resistance Evaluation of 10 Indoor Floor Surfaces
Cal Snow, Cody Hays, Sarah Girard, Lorri Birkenbuel, Daniel Autenrieth and David Gilkey
DOI10.61927/igmin199
Relationship between Sustainable Development, Economy and Poverty
Antonio Oñate Tenorio and María del os Santos Oñate Tenorio
DOI10.61927/igmin224
The Educational Role of Cinema in Physical Sciences
Maria Sagri, Denis Vavougios and Filippos Sofos
DOI10.61927/igmin121
Evaluating Digital Imaging Technologies for Anogenital Injury Documentation in Sexual Assault Cases
Jon Giolitti, Abbigail Behmlander, Sydney Brief, Emma Dixon, Sydney Hudock, Linda Rossman, Stephanie Solis, Meredith Busman, Lisa Ambrose, Lindsey Ouellette and Jeffrey Jones
DOI10.61927/igmin246
研究を公開する

私たちは、科学、技術、工学、医学に関する幅広い種類の記事を編集上の偏見なく公開しています。

提出する

見る 原稿のガイドライン 追加 論文処理料

IgMin 科目を探索する

Advertisement