Performance evaluation of vector evaluated gravitational search algorithm II

Performance evaluation of vector evaluated gravitational search algorithm II

This paper presents a performance evaluation of a novel Vector Evaluated Gravitational Search Algorithm II (VEGSAII) for multi-objective optimization problems. The VEGSAII algorithm uses a number of populations of particles. In particular, a population of particles corresponds to one objective funct...

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Bibliographic Details
Main Authors: Muhammad, B., Ibrahim, Z., Ghazali, K.H., Ghazali, M.R., Mubin, M., Mokhtar, M.
Format: Conference or Workshop Item
Language:English
Published: 2014
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.um.edu.my/13034/1/somet201414.pdf
Description
Summary:This paper presents a performance evaluation of a novel Vector Evaluated Gravitational Search Algorithm II (VEGSAII) for multi-objective optimization problems. The VEGSAII algorithm uses a number of populations of particles. In particular, a population of particles corresponds to one objective function to be minimized or maximized. Simultaneous minimization or maximization of every objective function is realized by exchanging a variable between populations. The results shows that the VEGSA is outperformed by other multi-objective optimization algorithms and further enhancements are needed before it can be employed in any application.

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