Advancements in Evolutionary Computation
A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Biochemistry, Biophysics and Computational Biology".
Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 252
Special Issue Editors
Interests: evolutionary computation; computer vision; path planning
Special Issue Information
Dear Colleagues,
Evolutionary computation, a family of algorithms inspired by biological evolution for global optimization, has been developed for a few decades. Evolutionary computation is used to solve complex optimization problems that have too many variables for traditional algorithms. Potential applications are wide-ranging and include problems from combinatorial optimization, multi-objective optimization, and numerical optimization in diverse domains, such as engineering, biology, medicine, robotics, etc. In particular, these problems are often noisy, stochastic, or have dynamically changing constraints. This is where evolutionary computation methods are often applied, as they have been shown to be highly successful when dealing with difficult problem domains. Evolutionary computation is commonly used instead of standard numerical methods when there is no known derivative of the fitness function or when the fitness function has many local extremes that can trap sequential methods.
There are many different techniques that can be used as part of evolutionary computation, e.g., genetic algorithms, genetic programming, evolution programming, evolutionary strategies, differential evolution, particle swarm optimization, ant colony optimization, and many other swarm intelligence algorithms.
This Special Issue explores how evolutionary computation methods can be utilized to analyze DNA, RNA, and protein sequences, including aspects such as sequence alignment, genomics, and protein structure prediction. We invite submissions on recent advances in the theory and applications of evolutionary computation in ecology, biology, drug design, and biomedical engineering.
We welcome all manuscripts primarily focused on bioscience, medicine, and plant aspects for submission to Life for further processing.
Dr. Leilei Cao
Dr. Shuwei Zhu
Guest Editors
Manuscript Submission Information
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Keywords
- evolutionary computation
- swarm intelligence
- genetic algorithms
- bio-inspired optimization
- particle swarm optimization
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