Ions motion optimization algorithm for multiobjective optimization problems

This paper offers a novel multiobjective approach – Multiobjective Ions Motion Optimization (MOIMO) algorithm stimulated by the movements of ions in nature. The main inspiration behind this approach is the force of attraction and repulsion between anions and cations. A storage and leader se...

Full description

Bibliographic Details
Main Authors: Buch, Hitarth, Trivedi, Indrajit
Format: Article
Language:English
Published: Growing Science 2021-01-01
Series:Decision Science Letters
Online Access:http://www.growingscience.com/dsl/Vol10/dsl_2020_41.pdf
id doaj-fc36bea2a34c4ca993b81e57b0c1976a
record_format Article
spelling doaj-fc36bea2a34c4ca993b81e57b0c1976a2021-01-01T14:15:41ZengGrowing ScienceDecision Science Letters1929-58041929-58122021-01-019311010.5267/j.dsl.2020.12.001Ions motion optimization algorithm for multiobjective optimization problemsBuch, HitarthTrivedi, Indrajit This paper offers a novel multiobjective approach – Multiobjective Ions Motion Optimization (MOIMO) algorithm stimulated by the movements of ions in nature. The main inspiration behind this approach is the force of attraction and repulsion between anions and cations. A storage and leader selection strategy is combined with the single objective Ions Motion Optimization (IMO) approach to estimate the Pareto optimum front for multiobjective optimization. The proposed method is applied to 18 different benchmark test functions to confirm its efficiency in finding optimal solutions. The outcomes are compared with three novel and well-accepted techniques in the literature using five performance parameters quantitatively and obtained Pareto fronts qualitatively. The comparison proves that MOIMO can approximate Pareto optimal solutions with good convergence and coverage with minimum computational time.http://www.growingscience.com/dsl/Vol10/dsl_2020_41.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Buch, Hitarth
Trivedi, Indrajit
spellingShingle Buch, Hitarth
Trivedi, Indrajit
Ions motion optimization algorithm for multiobjective optimization problems
Decision Science Letters
author_facet Buch, Hitarth
Trivedi, Indrajit
author_sort Buch, Hitarth
title Ions motion optimization algorithm for multiobjective optimization problems
title_short Ions motion optimization algorithm for multiobjective optimization problems
title_full Ions motion optimization algorithm for multiobjective optimization problems
title_fullStr Ions motion optimization algorithm for multiobjective optimization problems
title_full_unstemmed Ions motion optimization algorithm for multiobjective optimization problems
title_sort ions motion optimization algorithm for multiobjective optimization problems
publisher Growing Science
series Decision Science Letters
issn 1929-5804
1929-5812
publishDate 2021-01-01
description This paper offers a novel multiobjective approach – Multiobjective Ions Motion Optimization (MOIMO) algorithm stimulated by the movements of ions in nature. The main inspiration behind this approach is the force of attraction and repulsion between anions and cations. A storage and leader selection strategy is combined with the single objective Ions Motion Optimization (IMO) approach to estimate the Pareto optimum front for multiobjective optimization. The proposed method is applied to 18 different benchmark test functions to confirm its efficiency in finding optimal solutions. The outcomes are compared with three novel and well-accepted techniques in the literature using five performance parameters quantitatively and obtained Pareto fronts qualitatively. The comparison proves that MOIMO can approximate Pareto optimal solutions with good convergence and coverage with minimum computational time.
url http://www.growingscience.com/dsl/Vol10/dsl_2020_41.pdf
work_keys_str_mv AT buchhitarth ionsmotionoptimizationalgorithmformultiobjectiveoptimizationproblems
AT trivediindrajit ionsmotionoptimizationalgorithmformultiobjectiveoptimizationproblems
_version_ 1724364392305262592