NDLI: Probabilistically Driven Particle Swarms for Optimization of Multi Valued Discrete Problems : Design and Analysis

Content Provider	IEEE Xplore Digital Library
Author	Veeramachaneni, K. Osadciw, L. Kamath, G.
Copyright Year	2007
Description	Author affiliation: Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., NY (Veeramachaneni, K.; Osadciw, L.; Kamath, G.)
Abstract	A new particle swarm optimization (PSO) algorithm that is more effective for discrete, multi-valued optimization problems is presented. The new algorithm is probabilistically driven since it uses probabilistic transition rules to move from one discrete value to another in the search for an optimum solution. Properties of the binary discrete particle swarms are discussed. The new algorithm for discrete multi-values is designed with the similar properties. The algorithm is tested on a suite of benchmarks and comparisons are made between the binary PSO and the new discrete PSO implemented for ternary, quaternary systems. The results show that the new algorithm's performance is close and even slightly better than the original discrete, binary PSO designed by Kennedy and Eberhart. The algorithm can be used in any real world optimization problems, which have a discrete, bounded field
Starting Page	141
Ending Page	149
File Size	780123
Page Count	9
File Format	PDF
ISBN	1424407087
DOI	10.1109/SIS.2007.368038
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-04-01
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Computer science System testing Multidimensional systems Power engineering computing Benchmark testing Performance analysis Particle swarm optimization Design optimization Power engineering and energy
Content Type	Text
Resource Type	Article

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