Leader selection based Multi-Objective Flow Direction Algorithm (MOFDA): A novel approach for engineering design problems
Addressing complex real-world issues with conflicting objectives is a significant challenge in optimization. Practical algorithms must balance these objectives, mainly when decision-maker preferences are unclear. This paper introduces a multi-objective adaptation of the Flow Direction Algorithm (FDA...
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Elsevier
2025-03-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024019133 |
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| author | Nima Khodadadi Mohammad Ehteram Hojat Karami Mohammad H. Nadimi-Shahraki Laith Abualigah Seyedali Mirjalili |
| author_facet | Nima Khodadadi Mohammad Ehteram Hojat Karami Mohammad H. Nadimi-Shahraki Laith Abualigah Seyedali Mirjalili |
| author_sort | Nima Khodadadi |
| collection | DOAJ |
| description | Addressing complex real-world issues with conflicting objectives is a significant challenge in optimization. Practical algorithms must balance these objectives, mainly when decision-maker preferences are unclear. This paper introduces a multi-objective adaptation of the Flow Direction Algorithm (FDA) to address the shortcomings of traditional evolutionary and meta-heuristic optimization methods in multi-objective optimization (MOO). These conventional methods often fail to find Pareto optimal solutions and to represent all objectives fairly. Building on the FDA's success in single-objective tasks, we expanded its application to MOO, creating the Multi-Objective Flow Direction Algorithm (MOFDA). MOFDA incorporates new mechanisms to accurately and uniformly find optimal solutions for MOO challenges. It features a fixed-size external archive to maintain Pareto optimal solutions, uses a grid mechanism to improve non-dominated solutions within this archive, and implements a leader selection process to guide searches in the multi-objective space. These strategies enable MOFDA to discover superior solutions and ensure extensive coverage of the Pareto front. We validated MOFDA's effectiveness by testing it against 27 diverse problems using seven performance metrics. The results show MOFDA's ability to outperform well-known algorithms, achieving significant convergence and broad coverage, thus demonstrating its advanced capability in multi-objective optimization. The MOFDA source code is available at: https://nimakhodadadi.com/algorithms-%2B-codes. |
| format | Article |
| id | doaj-art-eef49e44e6bd4482a519632f2f7c9635 |
| institution | Kabale University |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-eef49e44e6bd4482a519632f2f7c96352024-12-19T11:00:19ZengElsevierResults in Engineering2590-12302025-03-0125103670Leader selection based Multi-Objective Flow Direction Algorithm (MOFDA): A novel approach for engineering design problemsNima Khodadadi0Mohammad Ehteram1Hojat Karami2Mohammad H. Nadimi-Shahraki3Laith Abualigah4Seyedali Mirjalili5Department of Civil and Architectural Engineering, University of Miami, Coral Gables, FL, USADepartment of Water Engineering and Hydraulic Structures, Faculty of Civil Engineering, Semnan University, Semnan, IranDepartment of Water Engineering and Hydraulic Structures, Faculty of Civil Engineering, Semnan University, Semnan, Iran; Corresponding author.Faculty of Computer Engineering, Najafabad Branch, Islamic Azad University, Najafabad 8514143131, IranComputer Science Department, Al al-Bayt University, Mafraq 25113, JordanCentre for Artificial Intelligence Research and Optimisation, Torrens University, Australia; University Research and Innovation Center (EKIK), Obuda University, Budapest, 1034, Hungary; Faculty of Electrical Engineering and Computer Science, VŠB-TU Ostrava, Czech Republic, Ostrava, 70080, Czech RepublicAddressing complex real-world issues with conflicting objectives is a significant challenge in optimization. Practical algorithms must balance these objectives, mainly when decision-maker preferences are unclear. This paper introduces a multi-objective adaptation of the Flow Direction Algorithm (FDA) to address the shortcomings of traditional evolutionary and meta-heuristic optimization methods in multi-objective optimization (MOO). These conventional methods often fail to find Pareto optimal solutions and to represent all objectives fairly. Building on the FDA's success in single-objective tasks, we expanded its application to MOO, creating the Multi-Objective Flow Direction Algorithm (MOFDA). MOFDA incorporates new mechanisms to accurately and uniformly find optimal solutions for MOO challenges. It features a fixed-size external archive to maintain Pareto optimal solutions, uses a grid mechanism to improve non-dominated solutions within this archive, and implements a leader selection process to guide searches in the multi-objective space. These strategies enable MOFDA to discover superior solutions and ensure extensive coverage of the Pareto front. We validated MOFDA's effectiveness by testing it against 27 diverse problems using seven performance metrics. The results show MOFDA's ability to outperform well-known algorithms, achieving significant convergence and broad coverage, thus demonstrating its advanced capability in multi-objective optimization. The MOFDA source code is available at: https://nimakhodadadi.com/algorithms-%2B-codes.http://www.sciencedirect.com/science/article/pii/S2590123024019133Multi-objective optimizationFlow Direction AlgorithmPareto optimality |
| spellingShingle | Nima Khodadadi Mohammad Ehteram Hojat Karami Mohammad H. Nadimi-Shahraki Laith Abualigah Seyedali Mirjalili Leader selection based Multi-Objective Flow Direction Algorithm (MOFDA): A novel approach for engineering design problems Results in Engineering Multi-objective optimization Flow Direction Algorithm Pareto optimality |
| title | Leader selection based Multi-Objective Flow Direction Algorithm (MOFDA): A novel approach for engineering design problems |
| title_full | Leader selection based Multi-Objective Flow Direction Algorithm (MOFDA): A novel approach for engineering design problems |
| title_fullStr | Leader selection based Multi-Objective Flow Direction Algorithm (MOFDA): A novel approach for engineering design problems |
| title_full_unstemmed | Leader selection based Multi-Objective Flow Direction Algorithm (MOFDA): A novel approach for engineering design problems |
| title_short | Leader selection based Multi-Objective Flow Direction Algorithm (MOFDA): A novel approach for engineering design problems |
| title_sort | leader selection based multi objective flow direction algorithm mofda a novel approach for engineering design problems |
| topic | Multi-objective optimization Flow Direction Algorithm Pareto optimality |
| url | http://www.sciencedirect.com/science/article/pii/S2590123024019133 |
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