Multi-Objective Majority–Minority Cellular Automata Algorithm for Global and Engineering Design Optimization
When dealing with complex models in real situations, many optimization problems require the use of more than one objective function to adequately represent the relevant characteristics of the system under consideration. Multi-objective optimization algorithms that can deal with several objective fun...
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2024-09-01
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| author | Juan Carlos Seck-Tuoh-Mora Ulises Hernandez-Hurtado Joselito Medina-Marín Norberto Hernández-Romero Liliana Lizárraga-Mendiola |
| author_facet | Juan Carlos Seck-Tuoh-Mora Ulises Hernandez-Hurtado Joselito Medina-Marín Norberto Hernández-Romero Liliana Lizárraga-Mendiola |
| author_sort | Juan Carlos Seck-Tuoh-Mora |
| collection | DOAJ |
| description | When dealing with complex models in real situations, many optimization problems require the use of more than one objective function to adequately represent the relevant characteristics of the system under consideration. Multi-objective optimization algorithms that can deal with several objective functions are necessary in order to obtain reasonable results within an adequate processing time. This paper presents the multi-objective version of a recent metaheuristic algorithm that optimizes a single objective function, known as the Majority–minority Cellular Automata Algorithm (MmCAA), inspired by cellular automata operations. The algorithm presented here is known as the Multi-objective Majority–minority Cellular Automata Algorithm (MOMmCAA). The MOMmCAA adds repository management and multi-objective search space density control to complement the performance of the MmCAA and make it capable of optimizing multi-objective problems. To evaluate the performance of the MOMmCAA, results on benchmark test sets (DTLZ, quadratic, and CEC-2020) and real-world engineering design problems were compared against other multi-objective algorithms recognized for their performance (MOLAPO, GS, MOPSO, NSGA-II, and MNMA). The results obtained in this work show that the MOMmCA achieves comparable performance with the other metaheuristic methods, demonstrating its competitiveness for use in multi-objective problems. The MOMmCAA was implemented in MATLAB and its source code can be consulted in GitHub. |
| format | Article |
| id | doaj-art-4f333f2cd3894d46a1105291683bf0b5 |
| institution | OA Journals |
| issn | 1999-4893 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | MDPI AG |
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| series | Algorithms |
| spelling | doaj-art-4f333f2cd3894d46a1105291683bf0b52025-08-20T02:11:11ZengMDPI AGAlgorithms1999-48932024-09-01171043310.3390/a17100433Multi-Objective Majority–Minority Cellular Automata Algorithm for Global and Engineering Design OptimizationJuan Carlos Seck-Tuoh-Mora0Ulises Hernandez-Hurtado1Joselito Medina-Marín2Norberto Hernández-Romero3Liliana Lizárraga-Mendiola4Academic Area of Engineering and Architecture, Institute of Basic Sciences and Engineering, Autonomous University of the State of Hidalgo, Pachuca 42184, Hidalgo, MexicoAcademic Area of Engineering and Architecture, Institute of Basic Sciences and Engineering, Autonomous University of the State of Hidalgo, Pachuca 42184, Hidalgo, MexicoAcademic Area of Engineering and Architecture, Institute of Basic Sciences and Engineering, Autonomous University of the State of Hidalgo, Pachuca 42184, Hidalgo, MexicoAcademic Area of Engineering and Architecture, Institute of Basic Sciences and Engineering, Autonomous University of the State of Hidalgo, Pachuca 42184, Hidalgo, MexicoAcademic Area of Engineering and Architecture, Institute of Basic Sciences and Engineering, Autonomous University of the State of Hidalgo, Pachuca 42184, Hidalgo, MexicoWhen dealing with complex models in real situations, many optimization problems require the use of more than one objective function to adequately represent the relevant characteristics of the system under consideration. Multi-objective optimization algorithms that can deal with several objective functions are necessary in order to obtain reasonable results within an adequate processing time. This paper presents the multi-objective version of a recent metaheuristic algorithm that optimizes a single objective function, known as the Majority–minority Cellular Automata Algorithm (MmCAA), inspired by cellular automata operations. The algorithm presented here is known as the Multi-objective Majority–minority Cellular Automata Algorithm (MOMmCAA). The MOMmCAA adds repository management and multi-objective search space density control to complement the performance of the MmCAA and make it capable of optimizing multi-objective problems. To evaluate the performance of the MOMmCAA, results on benchmark test sets (DTLZ, quadratic, and CEC-2020) and real-world engineering design problems were compared against other multi-objective algorithms recognized for their performance (MOLAPO, GS, MOPSO, NSGA-II, and MNMA). The results obtained in this work show that the MOMmCA achieves comparable performance with the other metaheuristic methods, demonstrating its competitiveness for use in multi-objective problems. The MOMmCAA was implemented in MATLAB and its source code can be consulted in GitHub.https://www.mdpi.com/1999-4893/17/10/433majority–minority cellular automata algorithm (MmCAA)multi-objective optimizationmetaheuristiccellular automatareal-world engineering problems |
| spellingShingle | Juan Carlos Seck-Tuoh-Mora Ulises Hernandez-Hurtado Joselito Medina-Marín Norberto Hernández-Romero Liliana Lizárraga-Mendiola Multi-Objective Majority–Minority Cellular Automata Algorithm for Global and Engineering Design Optimization Algorithms majority–minority cellular automata algorithm (MmCAA) multi-objective optimization metaheuristic cellular automata real-world engineering problems |
| title | Multi-Objective Majority–Minority Cellular Automata Algorithm for Global and Engineering Design Optimization |
| title_full | Multi-Objective Majority–Minority Cellular Automata Algorithm for Global and Engineering Design Optimization |
| title_fullStr | Multi-Objective Majority–Minority Cellular Automata Algorithm for Global and Engineering Design Optimization |
| title_full_unstemmed | Multi-Objective Majority–Minority Cellular Automata Algorithm for Global and Engineering Design Optimization |
| title_short | Multi-Objective Majority–Minority Cellular Automata Algorithm for Global and Engineering Design Optimization |
| title_sort | multi objective majority minority cellular automata algorithm for global and engineering design optimization |
| topic | majority–minority cellular automata algorithm (MmCAA) multi-objective optimization metaheuristic cellular automata real-world engineering problems |
| url | https://www.mdpi.com/1999-4893/17/10/433 |
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