Advances in Swarm Intelligence Optimization Algorithms and Applications: 2nd Edition

Dear Colleagues,

As industrialization continues to progress at an unprecedented pace, engineering applications are proliferating, accompanied by myriad intricate and diverse challenges. To navigate these complex real-world problems, a plethora of optimization algorithms have been devised, with swarm intelligence optimization algorithms (SIOAs) occupying a prominent position. SIOAs, drawing inspiration from the collective behaviors exhibited by swarms of insects, animals, and other organisms, have demonstrated remarkable abilities in solving non-convex, nonlinearly constrained, and high-dimensional optimization tasks. Their inherent capability to swiftly converge towards optimal solutions while effectively escaping local optima has been well documented in numerous studies.

This Special Issue, "Advances in Swarm Intelligence Optimization Algorithms and Applications: 2nd Edition", aims to consolidate and showcase the latest breakthroughs and achievements in this burgeoning field. It serves as a platform for interdisciplinary research, fostering collaboration among scholars from diverse backgrounds who are exploring the potential of SIOAs for engineering applications. We invite researchers to submit their original contributions that delve into the theoretical foundations, algorithmic innovations, and practical applications of SIOAs, with a focus on addressing specific challenges and advancing the state of the art of the field.

The scope of this Special Issue encompasses, but is not limited to, the following topics:

• Novel SIOAs: The development of new swarm intelligence optimization algorithms, including those inspired by unique swarm behaviors or innovative mechanisms for enhancing exploration, exploitation, and convergence.
• Hybridization and Integration: Studies exploring the integration of SIOAs with other optimization techniques, machine learning algorithms, or heuristic methods to create hybrid optimization frameworks that leverage the strengths of each approach.
• Theoretical Analysis: In-depth analyses of the mathematical properties, convergence behavior, and complexity of SIOAs, providing insights into their performance and limitations.
• Parameter Tuning and Adaptation: Research on adaptive parameter control strategies for SIOAs, aimed at enhancing their robustness, versatility, and performance across different problem domains.
• High-Dimensional and Complex Problems: Applications of SIOAs to tackle high-dimensional, multimodal, dynamic, and noisy optimization problems, demonstrating their effectiveness in real-world contexts.
• Benchmarking and Comparative Studies: Comparative evaluations of SIOAs using standard and novel benchmark functions, highlighting their strengths and weaknesses relative to other optimization techniques.
• Engineering Applications: Case studies showcasing the successful application of SIOAs in solving engineering problems, such as design optimization, production scheduling, network routing, and control systems.

By publishing high-quality research on SIOAs and their applications, this Special Issue aims to promote the dissemination of knowledge, facilitate interdisciplinary collaborations, and inspire further advancements in this exciting field. We encourage researchers to submit their original work, addressing both theoretical and applied aspects of SIOAs, to contribute to this important endeavor.

Prof. Dr. Heming Jia
Prof. Dr. Gang Hu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomimetics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• swarm intelligence optimization algorithms
• particle swarm optimization algorithm
• optimization algorithms
• meta-heuristics
• swarm intelligence
• engineering applications
• engineering design problems
• real-world applications
• constraint handling
• benchmarks
• novel approaches
• complicated optimization problems

• Advances in Swarm Intelligence Optimization Algorithms and Applications in Biomimetics (12 articles)