Particle Swarm Algorithms with Different Thermodynamics Mechanisms and Performance Comparison
نویسندگان
چکیده
منابع مشابه
Comparison of particle swarm optimization and tabu search algorithms for portfolio selection problem
Using Metaheuristics models and Evolutionary Algorithms for solving portfolio problem has been considered in recent years.In this study, by using particles swarm optimization and tabu search algorithms we optimized two-sided risk measures . A standard exact penalty function transforms the considered portfolio selection problem into an equivalent unconstrained minimization problem. And in final...
متن کاملPerformance Comparison of Particle Swarm Optimization with Traditional Clustering Algorithms used in Self-Organizing Map
Self-organizing map (SOM) is a well known data reduction technique used in data mining. It can reveal structure in data sets through data visualization that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOM...
متن کاملPerformance Comparison of Particle Swarm Optimization with Traditional Clustering Algorithms used in Self-Organizing Map
Self-organizing map (SOM) is a well known data reduction technique used in data mining. It can reveal structure in data sets through data visualization that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOM...
متن کاملComparison between Genetic Algorithms and Particle Swarm Optimization
This paper compares two evolutionary computation paradigms: genetic algorithms and particle swarm optimization. The operators of each paradigm are reviewed, focusing on how each affects search behavior in the problem space. The goals of the paper are to provide additional insights into how each paradigm works, and to suggest ways in which performance might be improved by incorporating features ...
متن کاملFactors Influencing Performance of Firefly and Particle Swarm Optimization Algorithms
In this paper, two nature inspired meta heuristic approaches particle swarm optimization and firefly algorithm are discussed. Both the approaches are population based approaches and has wide applications in various problems. Various factors influencing its performance is compared on the basis of selection of size of population, number of iterations, quality of solution, convergence criterion an...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Information Technology Journal
سال: 2014
ISSN: 1812-5638
DOI: 10.3923/itj.2014.1361.1365