Ions motion algorithm for solving optimization problems

Behzad Javidy; Abdolreza Hatamlou; Seyedali Mirjalili

doi:10.1016/j.asoc.2015.03.035

Ions motion algorithm for solving optimization problems

Behzad Javidy
, Abdolreza Hatamlou
, Seyedali Mirjalili

Research output: Contribution to journal › Article › peer-review

208 Citations (Scopus)

Abstract

Abstract This paper proposes a novel optimization algorithm inspired by the ions motion in nature. In fact, the proposed algorithm mimics the attraction and repulsion of anions and cations to perform optimization. The proposed algorithm is designed in such a way to have the least tuning parameters, low computational complexity, fast convergence, and high local optima avoidance. The performance of this algorithm is benchmarked on 10 standard test functions and compared to four well-known algorithms in the literature. The results demonstrate that the proposed algorithm is able to show very competitive results and has merits in solving challenging optimization problems.

Original language	English
Article number	2864
Pages (from-to)	72-79
Number of pages	8
Journal	Applied Soft Computing Journal
Volume	32
DOIs	https://doi.org/10.1016/j.asoc.2015.03.035
Publication status	Published - 1 Jul 2015
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities
SDG 12 Responsible Consumption and Production
SDG 13 Climate Action
SDG 17 Partnerships for the Goals

Keywords

Ions motion algorithm
Meta-heuristic algorithms
Optimization problems

Access to Document

10.1016/j.asoc.2015.03.035

Cite this

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title = "Ions motion algorithm for solving optimization problems",

abstract = "Abstract This paper proposes a novel optimization algorithm inspired by the ions motion in nature. In fact, the proposed algorithm mimics the attraction and repulsion of anions and cations to perform optimization. The proposed algorithm is designed in such a way to have the least tuning parameters, low computational complexity, fast convergence, and high local optima avoidance. The performance of this algorithm is benchmarked on 10 standard test functions and compared to four well-known algorithms in the literature. The results demonstrate that the proposed algorithm is able to show very competitive results and has merits in solving challenging optimization problems.",

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doi = "10.1016/j.asoc.2015.03.035",

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T1 - Ions motion algorithm for solving optimization problems

AU - Javidy, Behzad

AU - Hatamlou, Abdolreza

AU - Mirjalili, Seyedali

PY - 2015/7/1

Y1 - 2015/7/1

N2 - Abstract This paper proposes a novel optimization algorithm inspired by the ions motion in nature. In fact, the proposed algorithm mimics the attraction and repulsion of anions and cations to perform optimization. The proposed algorithm is designed in such a way to have the least tuning parameters, low computational complexity, fast convergence, and high local optima avoidance. The performance of this algorithm is benchmarked on 10 standard test functions and compared to four well-known algorithms in the literature. The results demonstrate that the proposed algorithm is able to show very competitive results and has merits in solving challenging optimization problems.

AB - Abstract This paper proposes a novel optimization algorithm inspired by the ions motion in nature. In fact, the proposed algorithm mimics the attraction and repulsion of anions and cations to perform optimization. The proposed algorithm is designed in such a way to have the least tuning parameters, low computational complexity, fast convergence, and high local optima avoidance. The performance of this algorithm is benchmarked on 10 standard test functions and compared to four well-known algorithms in the literature. The results demonstrate that the proposed algorithm is able to show very competitive results and has merits in solving challenging optimization problems.

KW - Ions motion algorithm

KW - Meta-heuristic algorithms

KW - Optimization problems

UR - https://www.scopus.com/pages/publications/84926431460

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DO - 10.1016/j.asoc.2015.03.035

M3 - Article

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SP - 72

EP - 79

JO - Applied Soft Computing Journal

JF - Applied Soft Computing Journal

M1 - 2864

ER -

Ions motion algorithm for solving optimization problems

Abstract

UN SDGs

Keywords

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