Please use this identifier to cite or link to this item:
https://olympias.lib.uoi.gr/jspui/handle/123456789/11213Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Tsoulos, I. G. | en |
| dc.contributor.author | Σταυρακούδης, Αθανάσιος | el |
| dc.date.accessioned | 2015-11-24T17:04:41Z | - |
| dc.date.available | 2015-11-24T17:04:41Z | - |
| dc.identifier.issn | 0096-3003 | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/11213 | - |
| dc.rights | Default Licence | - |
| dc.subject | global optimization | en |
| dc.subject | particle swarm optimization | en |
| dc.subject | stochastic methods | en |
| dc.subject | stopping rules | en |
| dc.subject | particle swarm optimization | en |
| dc.subject | differential evolution | en |
| dc.subject | multimodal functions | en |
| dc.subject | economic-dispatch | en |
| dc.subject | genetic algorithm | en |
| dc.subject | electromagnetics | en |
| dc.subject | generation | en |
| dc.subject | power | en |
| dc.title | Enhancing PSO methods for global optimization | en |
| heal.type | journalArticle | - |
| heal.type.en | Journal article | en |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.identifier.primary | DOI 10.1016/j.amc.2010.04.011 | - |
| heal.identifier.secondary | <Go to ISI>://000278542800020 | - |
| heal.language | en | - |
| heal.access | campus | - |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Οικονομικών και Κοινωνικών Επιστημών. Τμήμα Οικονομικών Επιστημών | el |
| heal.publicationDate | 2010 | - |
| heal.abstract | The Particle Swarm Optimization (PSO) method is a well-established technique for global optimization. During the past years several variations of the original PSO have been proposed in the relevant literature. Because of the increasing necessity in global optimization methods in almost all fields of science there is a great demand for efficient and fast implementations of relative algorithms. In this work we propose three modi. cations of the original PSO method in order to increase the speed and its efficiency that can be applied independently in almost every PSO variant. These modi. cations are: (a) a new stopping rule, (b) a similarity check and (c) a conditional application of some local search method. The proposed were tested using three popular PSO variants and a variety test functions. We have found that the application of these modi. cations resulted in significant gain in speed and efficiency. (C) 2010 Elsevier Inc. All rights reserved. | en |
| heal.journalName | Applied Mathematics and Computation | en |
| heal.journalType | peer reviewed | - |
| heal.fullTextAvailability | TRUE | - |
| Appears in Collections: | Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) - ΟΕ | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Stavrakoudis-2010-Enhancing PSO methods.pdf | 224.92 kB | Adobe PDF | View/Open Request a copy |
This item is licensed under a Creative Commons License
