Title: A conceptual comparison of NSGA-II, OMOPSO and AbYss algorithms

Authors: Rajani Kumari; Dinesh Kumar; Vijay Kumar

Addresses: Department of Computer Science and Engineering, Guru Jambheshwer University of Science and Technology, Hisar, Haryana-125001, India ' Department of Computer Science and Engineering, Guru Jambheshwer University of Science and Technology, Hisar, Haryana-125001, India ' Department of Computer Science and Engineering, Thapar University, Patiala, Punjab-147001, India

Abstract: The optimisation of multi-objective problems is currently an important area of research and development. The importance gained by this type of problem has given rise to the development of multi-objective metaheuristics to attain solutions for such problems. In this paper, an experimental comparison of non-dominated sorting genetic algorithm-II (NSGA-II), archive-based hybrid scatter search (AbYss), and optimised multi-objective particle swarm optimisation (OMOPSO) using ZDT benchmark, has been done to determine which multi-objective metaheuristic has the best performance with respect to a problem. The results thus obtained are compared and analysed based on three performance metrics namely hypervolume, GD, and IGD that evaluate the dispersion of the solutions on the Pareto front and its proximity to it.

Keywords: multi-objective optimisation; non-dominated sorting genetic algorithm-II; NSGA-II; archive-based hybrid scatter search; AbYss; optimised multi-objective particle swarm optimisation; OMOPSO.

DOI: 10.1504/IJITST.2017.10012598

International Journal of Internet Technology and Secured Transactions, 2017 Vol.7 No.4, pp.330 - 352

Received: 11 Apr 2017
Accepted: 17 May 2017
Published online: 04 May 2018 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article