A New Arithmetic Optimization Algorithm for Solving Real-World Multiobjective CEC-2021 Constrained Optimization Problems: Diversity Analysis and Validations
In this paper, a new Multi-Objective Arithmetic Optimization Algorithm (MOAOA) is proposed for solving Real-World constrained Multi-objective Optimization Problems (RWMOPs). Such problems can be found in different fields, including mechanical engineering, chemical engineering, process and synthesis,...
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doaj-0a9933e0e7e64576b00d80f4976086582021-06-16T23:00:24ZengIEEEIEEE Access2169-35362021-01-019842638429510.1109/ACCESS.2021.30855299445061A New Arithmetic Optimization Algorithm for Solving Real-World Multiobjective CEC-2021 Constrained Optimization Problems: Diversity Analysis and ValidationsManoharan Premkumar0https://orcid.org/0000-0003-1032-4634Pradeep Jangir1https://orcid.org/0000-0001-6944-4775Balan Santhosh Kumar2Ravichandran Sowmya3https://orcid.org/0000-0002-0967-7718Hassan Haes Alhelou4https://orcid.org/0000-0002-7427-2848Laith Abualigah5https://orcid.org/0000-0002-2203-4549Ali Riza Yildiz6Seyedali Mirjalili7https://orcid.org/0000-0002-1443-9458Department of Electrical and Electronics Engineering, Dayananda Sagar College of Engineering, Bengaluru, IndiaRajasthan Rajya Vidyut Prasaran Nigam Ltd., Sikar, IndiaDepartment of Computer Science and Engineering, Guru Nanak Institute of Technology, Hyderabad, IndiaDepartment of Electrical and Electronics Engineering, National Institute of Technology, Tiruchirapalli, IndiaDepartment of Electrical Power Engineering, Tishreen University, Lattakia, SyriaFaculty of Computer Sciences and Informatics, Amman Arab University, Amman, JordanDepartment of Automotive Engineering, Bursa Uludağ University, Bursa, TurkeyCentre for Artificial Intelligence Research and Optimisation, Torrens University Australia, Brisbane, QLD, AustraliaIn this paper, a new Multi-Objective Arithmetic Optimization Algorithm (MOAOA) is proposed for solving Real-World constrained Multi-objective Optimization Problems (RWMOPs). Such problems can be found in different fields, including mechanical engineering, chemical engineering, process and synthesis, and power electronics systems. MOAOA is inspired by the distribution behavior of the main arithmetic operators in mathematics. The proposed multi-objective version is formulated and developed from the recently introduced single-objective Arithmetic Optimization Algorithm (AOA) through an elitist non-dominance sorting and crowding distance-based mechanism. For the performance evaluation of MOAOA, a set of 35 constrained RWMOPs and five ZDT unconstrained problems are considered. For the fitness and efficiency evaluation of the proposed MOAOA, the results obtained from the MOAOA are compared with four other state-of-the-art multi-objective algorithms. In addition, five performance indicators, such as Hyper-Volume (HV), Spread (SD), Inverted Generational Distance (IGD), Runtime (RT), and Generational Distance (GD), are calculated for the rigorous evaluation of the performance and feasibility study of the MOAOA. The findings demonstrate the superiority of the MOAOA over other algorithms with high accuracy and coverage across all objectives. This paper also considers the Wilcoxon signed-rank test (WSRT) for the statistical investigation of the experimental study. The coverage, diversity, computational cost, and convergence behavior achieved by MOAOA show its high efficiency in solving ZDT and RWMOPs problems.https://ieeexplore.ieee.org/document/9445061/Arithmetic optimization algorithm (AOA)CEC-2021 real-world problemsconstrained optimizationmulti-objective arithmetic optimization algorithm (MOAOA) |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Manoharan Premkumar Pradeep Jangir Balan Santhosh Kumar Ravichandran Sowmya Hassan Haes Alhelou Laith Abualigah Ali Riza Yildiz Seyedali Mirjalili |
spellingShingle |
Manoharan Premkumar Pradeep Jangir Balan Santhosh Kumar Ravichandran Sowmya Hassan Haes Alhelou Laith Abualigah Ali Riza Yildiz Seyedali Mirjalili A New Arithmetic Optimization Algorithm for Solving Real-World Multiobjective CEC-2021 Constrained Optimization Problems: Diversity Analysis and Validations IEEE Access Arithmetic optimization algorithm (AOA) CEC-2021 real-world problems constrained optimization multi-objective arithmetic optimization algorithm (MOAOA) |
author_facet |
Manoharan Premkumar Pradeep Jangir Balan Santhosh Kumar Ravichandran Sowmya Hassan Haes Alhelou Laith Abualigah Ali Riza Yildiz Seyedali Mirjalili |
author_sort |
Manoharan Premkumar |
title |
A New Arithmetic Optimization Algorithm for Solving Real-World Multiobjective CEC-2021 Constrained Optimization Problems: Diversity Analysis and Validations |
title_short |
A New Arithmetic Optimization Algorithm for Solving Real-World Multiobjective CEC-2021 Constrained Optimization Problems: Diversity Analysis and Validations |
title_full |
A New Arithmetic Optimization Algorithm for Solving Real-World Multiobjective CEC-2021 Constrained Optimization Problems: Diversity Analysis and Validations |
title_fullStr |
A New Arithmetic Optimization Algorithm for Solving Real-World Multiobjective CEC-2021 Constrained Optimization Problems: Diversity Analysis and Validations |
title_full_unstemmed |
A New Arithmetic Optimization Algorithm for Solving Real-World Multiobjective CEC-2021 Constrained Optimization Problems: Diversity Analysis and Validations |
title_sort |
new arithmetic optimization algorithm for solving real-world multiobjective cec-2021 constrained optimization problems: diversity analysis and validations |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
In this paper, a new Multi-Objective Arithmetic Optimization Algorithm (MOAOA) is proposed for solving Real-World constrained Multi-objective Optimization Problems (RWMOPs). Such problems can be found in different fields, including mechanical engineering, chemical engineering, process and synthesis, and power electronics systems. MOAOA is inspired by the distribution behavior of the main arithmetic operators in mathematics. The proposed multi-objective version is formulated and developed from the recently introduced single-objective Arithmetic Optimization Algorithm (AOA) through an elitist non-dominance sorting and crowding distance-based mechanism. For the performance evaluation of MOAOA, a set of 35 constrained RWMOPs and five ZDT unconstrained problems are considered. For the fitness and efficiency evaluation of the proposed MOAOA, the results obtained from the MOAOA are compared with four other state-of-the-art multi-objective algorithms. In addition, five performance indicators, such as Hyper-Volume (HV), Spread (SD), Inverted Generational Distance (IGD), Runtime (RT), and Generational Distance (GD), are calculated for the rigorous evaluation of the performance and feasibility study of the MOAOA. The findings demonstrate the superiority of the MOAOA over other algorithms with high accuracy and coverage across all objectives. This paper also considers the Wilcoxon signed-rank test (WSRT) for the statistical investigation of the experimental study. The coverage, diversity, computational cost, and convergence behavior achieved by MOAOA show its high efficiency in solving ZDT and RWMOPs problems. |
topic |
Arithmetic optimization algorithm (AOA) CEC-2021 real-world problems constrained optimization multi-objective arithmetic optimization algorithm (MOAOA) |
url |
https://ieeexplore.ieee.org/document/9445061/ |
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