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http://dx.doi.org/10.7232/iems.2012.11.3.215

Comparison of Three Evolutionary Algorithms: GA, PSO, and DE  

Kachitvichyanukul, Voratas (Industrial and Manufacturing Engineering, Asian Institute of Technology)
Publication Information
Industrial Engineering and Management Systems / v.11, no.3, 2012 , pp. 215-223 More about this Journal
Abstract
This paper focuses on three very similar evolutionary algorithms: genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE). While GA is more suitable for discrete optimization, PSO and DE are more natural for continuous optimization. The paper first gives a brief introduction to the three EA techniques to highlight the common computational procedures. The general observations on the similarities and differences among the three algorithms based on computational steps are discussed, contrasting the basic performances of algorithms. Summary of relevant literatures is given on job shop, flexible job shop, vehicle routing, location-allocation, and multimode resource constrained project scheduling problems.
Keywords
Evolutionary Algorithm; Genetic Algorithm; Particle Swarm Optimization; Differential Evolution;
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Times Cited By KSCI : 1  (Citation Analysis)
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