Special Issue "Unconventional Methods for Particle Swarm Optimization"
Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 8752
Interests: machine learning; genetic programming; particle swarm optimization
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Particle swarm optimization (PSO) is a population-based optimization metaheuristic inspired by the collective dynamics of groups of animals, like insects, birds, and fishes. Recent research trends have indicated the potentiality of the approach and its large possibilities of improvement. With the term “unconventional methods for PSO”, here, we mean modifications of the standard PSO, with the objective of improving its performance, or bestowing on it some particular properties. For instance, new methods for choosing the inertia weight, constriction factor, cognition and social weights; parallelizing PSO in several different ways; defining hybrid algorithms in which PSO is integrated with other types of metaheuristic optimization methods; entropy-based PSO; etc. The study of unconventional methods for PSO is a very lively and active research field, and the objective of this Special Issue is to collect contributions in this recent and exciting area, with particular focus on entropic, information-theoretic, or probability theoretic techniques.
Prof. Dr. Leonardo Vanneschi
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. Entropy 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 1800 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.
- Entropy-based PSO
- Information Theory for PSO
- Probability Theory for PSO
- Theoretically motivated hybrid PSO systems
- Theoretically motivated parallelizations of PSO
- Theoretically motivated niching
- New accelertion strategies
- Automatic static and/or dynamic parameter setting
- Improvements and/or specializations of particle movements
- PSO for the optimization/improvement of machine learning methods
- Real-life applications using theortically motivated unconventional PSO systems