Multiobjective Ant Lion Approaches Applied to Electromagnetic Device Optimization
Nature-inspired metaheuristics of the swarm intelligence field are a powerful approach to solve electromagnetic optimization problems. Ant lion optimizer (ALO) is a nature-inspired stochastic metaheuristic that mimics the hunting behavior of ant lions using steps of random walk of ants, building tra...
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MDPI AG
2021-05-01
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| Series: | Technologies |
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| Online Access: | https://www.mdpi.com/2227-7080/9/2/35 |
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| author | Juliano Pierezan Leandro dos S. Coelho Viviana C. Mariani Sotirios K. Goudos Achilles D. Boursianis Nikolaos V. Kantartzis Christos. S. Antonopoulos Spiridon Nikolaidis |
| author_facet | Juliano Pierezan Leandro dos S. Coelho Viviana C. Mariani Sotirios K. Goudos Achilles D. Boursianis Nikolaos V. Kantartzis Christos. S. Antonopoulos Spiridon Nikolaidis |
| author_sort | Juliano Pierezan |
| collection | DOAJ |
| description | Nature-inspired metaheuristics of the swarm intelligence field are a powerful approach to solve electromagnetic optimization problems. Ant lion optimizer (ALO) is a nature-inspired stochastic metaheuristic that mimics the hunting behavior of ant lions using steps of random walk of ants, building traps, entrapment of ants in traps, catching preys, and re-building traps. To extend the classical single-objective ALO, this paper proposes four multiobjective ALO (MOALO) approaches using crowding distance, dominance concept for selecting the elite, and tournament selection mechanism with different schemes to select the leader. Numerical results from a multiobjective constrained brushless direct current (DC) motor design problem show that some MOALO approaches present promising performance in terms of Pareto-optimal solutions. |
| first_indexed | 2024-03-10T11:34:02Z |
| format | Article |
| id | doaj.art-c95d49b6211f4760b4578de923662927 |
| institution | Directory Open Access Journal |
| issn | 2227-7080 |
| language | English |
| last_indexed | 2024-03-10T11:34:02Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Technologies |
| spelling | doaj.art-c95d49b6211f4760b4578de9236629272023-11-21T19:04:50ZengMDPI AGTechnologies2227-70802021-05-01923510.3390/technologies9020035Multiobjective Ant Lion Approaches Applied to Electromagnetic Device OptimizationJuliano Pierezan0Leandro dos S. Coelho1Viviana C. Mariani2Sotirios K. Goudos3Achilles D. Boursianis4Nikolaos V. Kantartzis5Christos. S. Antonopoulos6Spiridon Nikolaidis7Department of Electrical Engineering, Federal University of Parana, Curitiba 80060-000, PR, BrazilDepartment of Electrical Engineering, Federal University of Parana, Curitiba 80060-000, PR, BrazilDepartment of Electrical Engineering, Federal University of Parana, Curitiba 80060-000, PR, BrazilELEDIA@AUTH, Department of Physics, Aristotle University of Thessaloniki, 54636 Thessaloniki, GreeceELEDIA@AUTH, Department of Physics, Aristotle University of Thessaloniki, 54636 Thessaloniki, GreeceDepartment of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54636 Thessaloniki, GreeceDepartment of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54636 Thessaloniki, GreeceELEDIA@AUTH, Department of Physics, Aristotle University of Thessaloniki, 54636 Thessaloniki, GreeceNature-inspired metaheuristics of the swarm intelligence field are a powerful approach to solve electromagnetic optimization problems. Ant lion optimizer (ALO) is a nature-inspired stochastic metaheuristic that mimics the hunting behavior of ant lions using steps of random walk of ants, building traps, entrapment of ants in traps, catching preys, and re-building traps. To extend the classical single-objective ALO, this paper proposes four multiobjective ALO (MOALO) approaches using crowding distance, dominance concept for selecting the elite, and tournament selection mechanism with different schemes to select the leader. Numerical results from a multiobjective constrained brushless direct current (DC) motor design problem show that some MOALO approaches present promising performance in terms of Pareto-optimal solutions.https://www.mdpi.com/2227-7080/9/2/35electromagnetic optimizationmultiobjective optimizationmetaheuristicsbrushless DC motor designant lion optimizer |
| spellingShingle | Juliano Pierezan Leandro dos S. Coelho Viviana C. Mariani Sotirios K. Goudos Achilles D. Boursianis Nikolaos V. Kantartzis Christos. S. Antonopoulos Spiridon Nikolaidis Multiobjective Ant Lion Approaches Applied to Electromagnetic Device Optimization Technologies electromagnetic optimization multiobjective optimization metaheuristics brushless DC motor design ant lion optimizer |
| title | Multiobjective Ant Lion Approaches Applied to Electromagnetic Device Optimization |
| title_full | Multiobjective Ant Lion Approaches Applied to Electromagnetic Device Optimization |
| title_fullStr | Multiobjective Ant Lion Approaches Applied to Electromagnetic Device Optimization |
| title_full_unstemmed | Multiobjective Ant Lion Approaches Applied to Electromagnetic Device Optimization |
| title_short | Multiobjective Ant Lion Approaches Applied to Electromagnetic Device Optimization |
| title_sort | multiobjective ant lion approaches applied to electromagnetic device optimization |
| topic | electromagnetic optimization multiobjective optimization metaheuristics brushless DC motor design ant lion optimizer |
| url | https://www.mdpi.com/2227-7080/9/2/35 |
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