SI-EA 2022 : Special Issue in Applied Sciences with IF 2.67 - Evolutionary Algorithms for large scale problems
SI-EA 2022 : Special Issue in Applied Sciences with IF 2.67 - Evolutionary Algorithms for large scale problems

SI-EA 2022 : Special Issue in Applied Sciences with IF 2.67 - Evolutionary Algorithms for large scale problems


Call for Papers

Dear Colleagues,

In the last decade, computational intelligence and, specifically, evolutionary computing research have witnessed exponential growth in terms of the strong pressure to search for and reinvent new optimization techniques based on nature-inspired phenomena. Similarly, we have also recently witnessed increased research efforts dedicated to addressing several complex real-world problems of either single-objective or multi-objective optimization orientation by using diverse evolutionary search strategies. However, despite the recorded success of these efforts in solving wide-ranging large-scale optimization problems, there is still a wide gap between the variety of application problems that have been addressed in the literature and those encountered in real life, which are significant for solving practical problems in science, medicine, and engineering. Moreover, due to the practical relevance of large-scale optimization problems, computationally efficient and effective evolutionary algorithms for solving such optimization problems are in high demand.

The Special Issue targets novel work that addresses recent advances in the following topics: theoretical analysis of evolutionary algorithms; evolutionary computation theory; evolutionary deep learning; hybrid evolutionary approaches; neuro-evolutionary systems; target-driven visual navigation; evolutionary algorithms for self-driving cars; parallel evolutionary algorithms; GPU implementation of evolutionary algorithms; target-driven visual navigation; evolutionary learning algorithms; neural architecture search; extreme learning machines; and few-shot learning, etc.

Therefore, in this Special Issue, we aim to promote discussions around recent efforts and advances in large-scale real-world applications of evolutionary algorithms to tackle challenging practical optimization problems. We encourage explorations of theory, applied research on the advancement of evolutionary algorithms, surveys, and comprehensive literature reviews.

Dr. Absalom Ezugwu
Dr. Haruna Chiroma
Dr. Laith Abualigah
Prof. Dr. Roberto A. Vazquez
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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 papers will be 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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2000 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.

genetic algorithm
genetic programming
evolutionary programming
evolution strategies
differential evolution
swarm intelligence
particle swarm optimization
artificial bee colony
ant colony optimization
artificial immune systems
memetic algorithms
large-scale optimization problems
evolutionary computation
cuckoo search algorithms
teaching learning-based optimization
sybiotic organisms search
whale optimization algorithm
butterfly optimization algorithm
ebola optimization search algorithm
Published Papers
This special issue is now open for submission.

Credits and Sources

[1] SI-EA 2022 : Special Issue in Applied Sciences with IF 2.67 - Evolutionary Algorithms for large scale problems

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