TY - JOUR
ID - 21888
TI - New Functions for Mass Calculation in Gravitational Search Algorithm
JO - Journal of Computing and Security
JA - JCS
LA - en
SN - 2322-4460
AU - Ebrahimi Mood, Sepehr
AU - Rashedi, Esmat
AU - Javidi, Mohammad Masoud
AD -
AD - Graduate university of advanced technology
AD - Shahid Bahonar University of Kerman
Y1 - 2015
PY - 2015
VL - 2
IS - 3
SP - 233
EP - 246
KW - Gravitational Search Algorithm
KW - Heuristic Search Algorithm
KW - Scaling Functions
KW - Exploration and Exploitation
KW - Mass Calculation
DO -
N2 - Nowadays, optimization problems are large-scale and complicated, so heuristic optimization algorithms have become common for solving them. Gravitational Search Algorithm (GSA) is one of the heuristic algorithms for solving optimization problems inspired by Newton's lows of gravity and motion. Definition and calculation of masses in GSA have an impact on the performance of the algorithm. Defining appropriate functions for mass calculation improves the exploitation and exploration power of the algorithm and prevents the algorithm from getting trapped in local optima. In this paper, Sigma scaling and Boltzmann selection functions are examined for mass calculation in GSA. The proposed functions are evaluated on some standard test functions including unimodal functions and multimodal functions. The obtained results are compared with the standard GSA, genetic algorithm, particle swarm optimization algorithm, gravitational particle swarm algorithm and clustered-GSA. Experimental results show that the proposed method outperforms the state-of-the-art optimization algorithms, despite the simplicity of implementation.
UR - http://jcomsec.ui.ac.ir/article_21888.html
L1 - http://jcomsec.ui.ac.ir/article_21888_f8fde39da818127ec8e4eaf51525b2bf.pdf
ER -