Title : ( A nature-inspired transition from Differential Evolution to Particle Swarm Optimization )
Authors: Hooman Khosravi , Mahdi Abolfazli Esfahani , Mohammad Reza Akbarzadeh Totonchi ,
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Abstract
In recent years, Differential Evolution (DE) has been successfully utilized for solving multidimensional and complex optimization problems, due to its easy implementation and simplicity. Yet, similar to many other optimization algorithms, DE suffers from the problem of stagnation and lack of convergence. In contrast, Particle Swarm Optimization (PSO) has good properties in terms of its population convergence. Our proposed method is a transition from DE to PSO by using a nature inspired temperature model; same temperature model has been used in many methods such as Simulated Annealing (SA). By using our method, we benefit from both the fast speed of DE and the convergence power of PSO.
Keywords
Differential Evolution (DE); Particle Swarm Optimization (PSO); Simulated Annealing (SA); Temperature Model; Hybrid Optimization
@inproceedings{paperid:1054885,
author = {Khosravi, Hooman and Abolfazli Esfahani, Mahdi and Akbarzadeh Totonchi, Mohammad Reza},
title = {A nature-inspired transition from Differential Evolution to Particle Swarm Optimization},
booktitle = {Computer and Knowledge Engineering (ICCKE), 2015 5th International Conference on},
year = {2015},
location = {مشهد, IRAN},
keywords = {Differential Evolution (DE); Particle Swarm
Optimization (PSO); Simulated Annealing (SA); Temperature
Model; Hybrid Optimization},
}
%0 Conference Proceedings
%T A nature-inspired transition from Differential Evolution to Particle Swarm Optimization
%A Khosravi, Hooman
%A Abolfazli Esfahani, Mahdi
%A Akbarzadeh Totonchi, Mohammad Reza
%J Computer and Knowledge Engineering (ICCKE), 2015 5th International Conference on
%D 2015
