DocumentCode :
1792453
Title :
A novel toolbox for advanced particle swarm optimization based industrial applications
Author :
Nicolosi, Leonardo ; Brusaferri, Alessandro ; Ballarino, A.
Author_Institution :
Inst. of Ind. Technol. & Autom., Milan, Italy
fYear :
2014
fDate :
16-19 Sept. 2014
Firstpage :
1
Lastpage :
8
Abstract :
Particle swarm optimization (PSO) is a stochastic algorithm conceived to solve complex optimization problems. Since its first appearance, different models of PSO have been proposed, in order to improve its search characteristics. Despite the results in literature are very promising, PSO has not been deeply applied within the industrial domain, mainly due to the lack of integrated tools conceived to properly supporting development activities. The present paper proposes a new Matlab Graphical User Interface (GUI) based toolbox for agile PSO industrial solution engineering, including best performing PSO models. Simulation based validated solutions can be agilely deployed and integrated within industrial platforms by means of C/C++ code generation. Moreover, toolbox capabilities and usability are demonstrated on benchmark tests and on a pilot industrial application.
Keywords :
C++ language; graphical user interfaces; particle swarm optimisation; production engineering computing; program compilers; search problems; stochastic programming; C/C++ code generation; GUI based toolbox; Matlab graphical user interface based toolbox; PSO model; advanced particle swarm optimization based industrial applications; agile PSO industrial solution engineering; complex optimization problems; industrial domain; industrial platforms; pilot industrial application; search characteristics; stochastic algorithm; toolbox capabilities; toolbox usability; Acceleration; Graphical user interfaces; Linear programming; MATLAB; Mathematical model; Optimization; Particle swarm optimization; industrial control; industry applications; optimization methods; particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Technology and Factory Automation (ETFA), 2014 IEEE
Conference_Location :
Barcelona
Type :
conf
DOI :
10.1109/ETFA.2014.7005162
Filename :
7005162
Link To Document :
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