scholarly journals Application of Multi-objective Charged System Search Algorithm for Optimization Problems

2018 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
S. Talatahari ◽  
F. Hakimpour ◽  
A. Ranjbar
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Multi Objective ◽  
Charged System Search ◽  
Charged System

A Strength Pareto Gravitational Search Algorithm for Multi-Objective Optimization Problems

2015 ◽  
Vol 29 (06) ◽  
pp. 1559010 ◽  
Author(s):  
Xiaohui Yuan ◽  
Zhihuan Chen ◽  
Yanbin Yuan ◽  
Yuehua Huang ◽  
Xiaopan Zhang
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Population Diversity ◽  
Benchmark Problems ◽  
Multi Objective Optimization ◽  
Local Optima ◽  
Multi Objective ◽  
Fine Grained ◽  
Gravitational Search

A novel strength Pareto gravitational search algorithm (SPGSA) is proposed to solve multi-objective optimization problems. This SPGSA algorithm utilizes the strength Pareto concept to assign the fitness values for agents and uses a fine-grained elitism selection mechanism to keep the population diversity. Furthermore, the recombination operators are modeled in this approach to decrease the possibility of trapping in local optima. Experiments are conducted on a series of benchmark problems that are characterized by difficulties in local optimality, nonuniformity, and nonconvexity. The results show that the proposed SPGSA algorithm performs better in comparison with other related works. On the other hand, the effectiveness of two subtle means added to the GSA are verified, i.e. the fine-grained elitism selection and the use of SBX and PMO operators. Simulation results show that these measures not only improve the convergence ability of original GSA, but also preserve the population diversity adequately, which enables the SPGSA algorithm to have an excellent ability that keeps a desirable balance between the exploitation and exploration so as to accelerate the convergence speed to the true Pareto-optimal front.

Novel Adaptive Charged System Search algorithm for optimal tuning of fuzzy controllers

2014 ◽  
Vol 41 (4) ◽  
pp. 1168-1175 ◽  
Author(s):  
Radu-Emil Precup ◽  
Radu-Codruţ David ◽  
Emil M. Petriu ◽  
Stefan Preitl ◽  
Mircea-Bogdan Rădac
Keyword(s):  
Search Algorithm ◽  
Fuzzy Controllers ◽  
Optimal Tuning ◽  
Charged System Search ◽  
Charged System
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