MAOA: A Swift and Effective Optimization Algorithm for Linear Antenna Array Design
This paper presents the modified arithmetic optimization algorithm (MAOA), a swift and effective optimization algorithm specifically designed for electromagnetic applications. Its primary advantage is its ability to avoid local minima by striking a balance between global exploration and local exploi...
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2025-05-01
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| author | Anoop Raghuvanshi Abhinav Sharma Abhishek Kumar Awasthi Abhishek Sharma Rahul Singhal Kim Soon Chong Sew Sun Tiang Wei Hong Lim |
| author_facet | Anoop Raghuvanshi Abhinav Sharma Abhishek Kumar Awasthi Abhishek Sharma Rahul Singhal Kim Soon Chong Sew Sun Tiang Wei Hong Lim |
| author_sort | Anoop Raghuvanshi |
| collection | DOAJ |
| description | This paper presents the modified arithmetic optimization algorithm (MAOA), a swift and effective optimization algorithm specifically designed for electromagnetic applications. Its primary advantage is its ability to avoid local minima by striking a balance between global exploration and local exploitation searches. This equilibrium is maintained through three key improvements: an enhanced initialization process, a distinctive guidance mechanism for steering searches, and an additional learning phase to refine newly found solutions. This process innovation significantly boosts MAOA’s performance in addressing both constrained and unconstrained optimization challenges. In this study, MAOA is applied to optimize the spacing and current amplitude of linear antenna array (LAA) elements, with the goal of minimizing peak side lobe level (PSLL), close-in side lobe level (CSLL), and overall side lobe level (SLL), both with and without constraints on first null beamwidth (FNBW), as well as null positioning with SLL minimization. Ten designs, comprising 10 and 20 antenna elements of LAA and one 14-element circular antenna array (CAA), showcase MAOA’s proficiency in antenna array pattern synthesis. Optimizing element positions results in a PSLL of −21.28 dB, a CSLL of −34.50 dB, and a null depth of −89.00 dB, while optimizing current amplitude achieves a PSLL of −24.32 dB, a CSLL of −29.73 dB, and a null depth of −77.60 dB across various antenna designs. Simulation results reveal that MAOA significantly surpasses traditional uniform linear arrays (ULA) and established optimization techniques. Its superiority is further confirmed through a Wilcoxon rank-sum and Friedman test. |
| format | Article |
| id | doaj-art-e99ea98880fb4b78ae2f7c9966950f78 |
| institution | Kabale University |
| issn | 2673-4001 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Telecom |
| spelling | doaj-art-e99ea98880fb4b78ae2f7c9966950f782025-08-20T03:29:47ZengMDPI AGTelecom2673-40012025-05-01623410.3390/telecom6020034MAOA: A Swift and Effective Optimization Algorithm for Linear Antenna Array DesignAnoop Raghuvanshi0Abhinav Sharma1Abhishek Kumar Awasthi2Abhishek Sharma3Rahul Singhal4Kim Soon Chong5Sew Sun Tiang6Wei Hong Lim7Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun 248007, Uttarakhand, IndiaDepartment of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun 248007, Uttarakhand, IndiaParas Antidrone Technologies Private Limited, Navi Mumbai 400706, Maharashtra, IndiaDepartment of Computer Science and Engineering, Graphic Era Deemed to Be University, Dehradun 248002, Uttarakhand, IndiaDepartment of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun 248007, Uttarakhand, IndiaFaculty of Engineering, Technology and Built Environment, UCSI University, Kuala Lumpur 56000, MalaysiaFaculty of Engineering, Technology and Built Environment, UCSI University, Kuala Lumpur 56000, MalaysiaFaculty of Engineering, Technology and Built Environment, UCSI University, Kuala Lumpur 56000, MalaysiaThis paper presents the modified arithmetic optimization algorithm (MAOA), a swift and effective optimization algorithm specifically designed for electromagnetic applications. Its primary advantage is its ability to avoid local minima by striking a balance between global exploration and local exploitation searches. This equilibrium is maintained through three key improvements: an enhanced initialization process, a distinctive guidance mechanism for steering searches, and an additional learning phase to refine newly found solutions. This process innovation significantly boosts MAOA’s performance in addressing both constrained and unconstrained optimization challenges. In this study, MAOA is applied to optimize the spacing and current amplitude of linear antenna array (LAA) elements, with the goal of minimizing peak side lobe level (PSLL), close-in side lobe level (CSLL), and overall side lobe level (SLL), both with and without constraints on first null beamwidth (FNBW), as well as null positioning with SLL minimization. Ten designs, comprising 10 and 20 antenna elements of LAA and one 14-element circular antenna array (CAA), showcase MAOA’s proficiency in antenna array pattern synthesis. Optimizing element positions results in a PSLL of −21.28 dB, a CSLL of −34.50 dB, and a null depth of −89.00 dB, while optimizing current amplitude achieves a PSLL of −24.32 dB, a CSLL of −29.73 dB, and a null depth of −77.60 dB across various antenna designs. Simulation results reveal that MAOA significantly surpasses traditional uniform linear arrays (ULA) and established optimization techniques. Its superiority is further confirmed through a Wilcoxon rank-sum and Friedman test.https://www.mdpi.com/2673-4001/6/2/34pattern synthesisarithmetic optimization algorithmoptimizationLAAwilcoxonfriedman |
| spellingShingle | Anoop Raghuvanshi Abhinav Sharma Abhishek Kumar Awasthi Abhishek Sharma Rahul Singhal Kim Soon Chong Sew Sun Tiang Wei Hong Lim MAOA: A Swift and Effective Optimization Algorithm for Linear Antenna Array Design Telecom pattern synthesis arithmetic optimization algorithm optimization LAA wilcoxon friedman |
| title | MAOA: A Swift and Effective Optimization Algorithm for Linear Antenna Array Design |
| title_full | MAOA: A Swift and Effective Optimization Algorithm for Linear Antenna Array Design |
| title_fullStr | MAOA: A Swift and Effective Optimization Algorithm for Linear Antenna Array Design |
| title_full_unstemmed | MAOA: A Swift and Effective Optimization Algorithm for Linear Antenna Array Design |
| title_short | MAOA: A Swift and Effective Optimization Algorithm for Linear Antenna Array Design |
| title_sort | maoa a swift and effective optimization algorithm for linear antenna array design |
| topic | pattern synthesis arithmetic optimization algorithm optimization LAA wilcoxon friedman |
| url | https://www.mdpi.com/2673-4001/6/2/34 |
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