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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Published in:	IEEE access Vol. 9; pp. 84263 - 84295
Main Authors:	Premkumar, Manoharan, Jangir, Pradeep, Kumar, Balan Santhosh, Sowmya, Ravichandran, Alhelou, Hassan Haes, Abualigah, Laith, Yildiz, Ali Riza, Mirjalili, Seyedali
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Arithmetic Arithmetic optimization algorithm (AOA) CEC-2021 real-world problems Chemical engineering Chemical synthesis constrained optimization Convergence Feasibility studies Genetic algorithms Mechanical engineering multi-objective arithmetic optimization algorithm (MOAOA) Multiple objective analysis Operators (mathematics) Optimization Optimization algorithms Pareto optimization Performance evaluation Rank tests Sorting Sorting algorithms Task analysis
ISSN:	2169-3536, 2169-3536
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Abstract	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.
AbstractList	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.
Author	Yildiz, Ali Riza Kumar, Balan Santhosh Premkumar, Manoharan Alhelou, Hassan Haes Sowmya, Ravichandran Abualigah, Laith Jangir, Pradeep Mirjalili, Seyedali
Author_xml	– sequence: 1 givenname: Manoharan orcidid: 0000-0003-1032-4634 surname: Premkumar fullname: Premkumar, Manoharan email: mprem.me@gmail.com organization: Department of Electrical and Electronics Engineering, Dayananda Sagar College of Engineering, Bengaluru, India – sequence: 2 givenname: Pradeep orcidid: 0000-0001-6944-4775 surname: Jangir fullname: Jangir, Pradeep organization: Rajasthan Rajya Vidyut Prasaran Nigam Ltd., Sikar, India – sequence: 3 givenname: Balan Santhosh surname: Kumar fullname: Kumar, Balan Santhosh organization: Department of Computer Science and Engineering, Guru Nanak Institute of Technology, Hyderabad, India – sequence: 4 givenname: Ravichandran orcidid: 0000-0002-0967-7718 surname: Sowmya fullname: Sowmya, Ravichandran organization: Department of Electrical and Electronics Engineering, National Institute of Technology, Tiruchirapalli, India – sequence: 5 givenname: Hassan Haes orcidid: 0000-0002-7427-2848 surname: Alhelou fullname: Alhelou, Hassan Haes email: alhelou@ieee.org organization: Department of Electrical Power Engineering, Tishreen University, Lattakia, Syria – sequence: 6 givenname: Laith orcidid: 0000-0002-2203-4549 surname: Abualigah fullname: Abualigah, Laith organization: Faculty of Computer Sciences and Informatics, Amman Arab University, Amman, Jordan – sequence: 7 givenname: Ali Riza surname: Yildiz fullname: Yildiz, Ali Riza organization: Department of Automotive Engineering, Bursa Uludağ University, Bursa, Turkey – sequence: 8 givenname: Seyedali orcidid: 0000-0002-1443-9458 surname: Mirjalili fullname: Mirjalili, Seyedali organization: Centre for Artificial Intelligence Research and Optimisation, Torrens University Australia, Brisbane, QLD, Australia
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Snippet	In this paper, a new Multi-Objective Arithmetic Optimization Algorithm (MOAOA) is proposed for solving Real-World constrained Multi-objective Optimization...
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SubjectTerms	Arithmetic Arithmetic optimization algorithm (AOA) CEC-2021 real-world problems Chemical engineering Chemical synthesis constrained optimization Convergence Feasibility studies Genetic algorithms Mechanical engineering multi-objective arithmetic optimization algorithm (MOAOA) Multiple objective analysis Operators (mathematics) Optimization Optimization algorithms Pareto optimization Performance evaluation Rank tests Sorting Sorting algorithms Task analysis
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Title	A New Arithmetic Optimization Algorithm for Solving Real-World Multiobjective CEC-2021 Constrained Optimization Problems: Diversity Analysis and Validations
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