Analysis of Reliability and Cost of Complex Systems with Metaheuristic Algorithms
Introduction. The assessment of the reliability and cost of complex systems, such as Complex Bridge Systems (CBS) and Life Support Systems in Space Capsules (LSSSC), is fascinating. To achieve the ideal system design through diverse constraints and increase overall system reliability, researchers ha...
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| Дата: | 2024 |
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| Мова: | English |
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Dr. Viktor Koval
2024
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| Назва журналу: | Economics Ecology Socium |
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oai:ojs2.www.ees-journal.com:article-2392024-03-27T09:17:36Z Analysis of Reliability and Cost of Complex Systems with Metaheuristic Algorithms Choudhary, Shivani Ram, Mangey Goyal, Nupur Saini, Seema CBS, LSSSC, cost, reliability, metaheuristic algorithms. Introduction. The assessment of the reliability and cost of complex systems, such as Complex Bridge Systems (CBS) and Life Support Systems in Space Capsules (LSSSC), is fascinating. To achieve the ideal system design through diverse constraints and increase overall system reliability, researchers have extensively explored system reliability and cost optimization problems. Hence, the significant advancement in metaheuristic methods is the primary source of further system reliability and cost optimization process refinement. Aim and tasks. This research attempts to enhance the reliability and cost of complex systems named CBC and LSSSC has been presented. Results. The structure is based on few recent metaheuristic techniques, such as Moth Flame Optimization (MFO), Whale Optimization Algorithm (WOA), Gazelle Optimization Algorithm (GOA), Dragonfly Algorithm (DA), and Coati Optimization Algorithm (COA). Comparing the acquired findings to those found in other proposed techniques demonstrates the usefulness of a methodology based on COA. The proposed COA algorithm exhibits enhanced efficiency by offering superior solutions to reliability and cost-optimization problems. In addition, a non-parametric Friedman ranking was performed for validation. The results of this research are based on improving the reliability of the parameters and decreasing complex systems’ costs used by the five metaheuristic methods. Observing the convergence graph, Friedman ranking, statistical results test, and tables determined that COA is the most effective algorithm for a complex system’s cost and reliability parameters compared to other existing approaches, and also provided a faster solution. Conclusions. This study proposes unique ways to reduce costs while increasing parameter reliability in complex systems. After analysing the comparative solution, the authors found that when comparing these approaches (GOA, DA, MFO, WOA, and COA), the COA provided the best minimum solution for the cost and reliability of complex systems. Hence, the suggested COA procedure was more successful than that described in this study. Dr. Viktor Koval 2024-03-30 Article Article Peer-reviewed Article application/pdf https://ees-journal.com/index.php/journal/article/view/239 10.61954/2616-7107/2024.8.1-1 Economics Ecology Socium; Vol. 8 No. 1 (2024): Economics. Ecology. Socium; 1-15 Економіка Екологія Соціум; Том 8 № 1 (2024): Economics. Ecology. Socium; 1-15 2616-7107 2616-7107 10.61954/2616-7107/2024.8.1 en https://ees-journal.com/index.php/journal/article/view/239/201 Copyright (c) 2024 Economics. Ecology. Socium |
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Economics Ecology Socium |
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| datestamp_date |
2024-03-27T09:17:36Z |
| collection |
OJS |
| language |
English |
| topic_facet |
CBS LSSSC cost reliability metaheuristic algorithms. |
| format |
Article |
| author |
Choudhary, Shivani Ram, Mangey Goyal, Nupur Saini, Seema |
| spellingShingle |
Choudhary, Shivani Ram, Mangey Goyal, Nupur Saini, Seema Analysis of Reliability and Cost of Complex Systems with Metaheuristic Algorithms |
| author_facet |
Choudhary, Shivani Ram, Mangey Goyal, Nupur Saini, Seema |
| author_sort |
Choudhary, Shivani |
| title |
Analysis of Reliability and Cost of Complex Systems with Metaheuristic Algorithms |
| title_short |
Analysis of Reliability and Cost of Complex Systems with Metaheuristic Algorithms |
| title_full |
Analysis of Reliability and Cost of Complex Systems with Metaheuristic Algorithms |
| title_fullStr |
Analysis of Reliability and Cost of Complex Systems with Metaheuristic Algorithms |
| title_full_unstemmed |
Analysis of Reliability and Cost of Complex Systems with Metaheuristic Algorithms |
| title_sort |
analysis of reliability and cost of complex systems with metaheuristic algorithms |
| description |
Introduction. The assessment of the reliability and cost of complex systems, such as Complex Bridge Systems (CBS) and Life Support Systems in Space Capsules (LSSSC), is fascinating. To achieve the ideal system design through diverse constraints and increase overall system reliability, researchers have extensively explored system reliability and cost optimization problems. Hence, the significant advancement in metaheuristic methods is the primary source of further system reliability and cost optimization process refinement.
Aim and tasks. This research attempts to enhance the reliability and cost of complex systems named CBC and LSSSC has been presented.
Results. The structure is based on few recent metaheuristic techniques, such as Moth Flame Optimization (MFO), Whale Optimization Algorithm (WOA), Gazelle Optimization Algorithm (GOA), Dragonfly Algorithm (DA), and Coati Optimization Algorithm (COA). Comparing the acquired findings to those found in other proposed techniques demonstrates the usefulness of a methodology based on COA. The proposed COA algorithm exhibits enhanced efficiency by offering superior solutions to reliability and cost-optimization problems. In addition, a non-parametric Friedman ranking was performed for validation. The results of this research are based on improving the reliability of the parameters and decreasing complex systems’ costs used by the five metaheuristic methods. Observing the convergence graph, Friedman ranking, statistical results test, and tables determined that COA is the most effective algorithm for a complex system’s cost and reliability parameters compared to other existing approaches, and also provided a faster solution.
Conclusions. This study proposes unique ways to reduce costs while increasing parameter reliability in complex systems. After analysing the comparative solution, the authors found that when comparing these approaches (GOA, DA, MFO, WOA, and COA), the COA provided the best minimum solution for the cost and reliability of complex systems. Hence, the suggested COA procedure was more successful than that described in this study. |
| publisher |
Dr. Viktor Koval |
| publishDate |
2024 |
| url |
https://ees-journal.com/index.php/journal/article/view/239 |
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2025-09-24T17:26:35Z |
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2025-12-02T15:32:10Z |
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