A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties
Multiobjective reliability-redundancy allocation problem (MORRAP) needs to maximize system reliability and minimize cost, weight, and volume with underlining constraints. In the systems’ design and analysis phase, uncertainties can occur from various sources, such as manufacturing variabi...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10052664/ |
| _version_ | 1811158486053027840 |
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| author | Zubair Ashraf Mohammad Shahid Faisal Ahamd Mohammad Sajid Ketan Kotecha Shruti Patil |
| author_facet | Zubair Ashraf Mohammad Shahid Faisal Ahamd Mohammad Sajid Ketan Kotecha Shruti Patil |
| author_sort | Zubair Ashraf |
| collection | DOAJ |
| description | Multiobjective reliability-redundancy allocation problem (MORRAP) needs to maximize system reliability and minimize cost, weight, and volume with underlining constraints. In the systems’ design and analysis phase, uncertainties can occur from various sources, such as manufacturing variability, environmental conditions, user behavior, etc. To deal with this, we present a generalization of the traditional MORRAP under multiple empirical and ambiguous circumstances, named interval type-2 fuzzy multiobjective reliability redundancy allocation problem (IT2FMORRAP). The newly formulated IT2FMORRAP considers optimizing goals as reliability, cost, and weight for a series-parallel system with interval type-2 fuzzy number. The mathematical formulation is established under which the proposed IT2FMORRAP model reduces to T1FMORRAP (type-1 fuzzy MORRAP), IVMORRAP (interval-valued MORRAP), and classical MORRAP. An Enhanced Karnik-Mendel and NSGA-II algorithm-based solving strategy is developed for the proposed IT2FMORRAP. The real-world dataset is considered to demonstrate the efficacy of the solution method for the proposed problem. A K-mean clustering technique identifies the best solution sets from the knee region of the generated Pareto fronts. An experimental study on commonly used performance metrics reveals that IT2FMORRAP performs significantly better than T1FMORRAP and crisp MORRAP. Further, the statistical analysis also confirms the hypothesis established in the empirical research. Finally, a comparative performance study has been conducted with notable state-of-the-art papers from the literature to encounter an appropriate establishment for the proposed work in the domain. |
| first_indexed | 2024-04-10T05:25:32Z |
| format | Article |
| id | doaj.art-285646ee06b44de4b23e10d772c77c9d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-10T05:25:32Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-285646ee06b44de4b23e10d772c77c9d2023-03-08T00:00:11ZengIEEEIEEE Access2169-35362023-01-0111215752159910.1109/ACCESS.2023.324880010052664A Generalized Multiobjective Reliability Redundancy Allocation With UncertaintiesZubair Ashraf0https://orcid.org/0000-0001-7122-2856Mohammad Shahid1https://orcid.org/0000-0002-4081-5963Faisal Ahamd2Mohammad Sajid3https://orcid.org/0000-0001-8822-5332Ketan Kotecha4https://orcid.org/0000-0003-2653-3780Shruti Patil5https://orcid.org/0000-0002-4903-1540Department of Computer Engineering and Application, GLA University, Mathura, Uttar Pradesh, IndiaDepartment of Commerce, Aligarh Muslim University, Aligarh, IndiaWorkday Inc., Pleasanton, CA, USADepartment of Computer Science, Aligarh Muslim University, Aligarh, IndiaSymbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, IndiaSymbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, IndiaMultiobjective reliability-redundancy allocation problem (MORRAP) needs to maximize system reliability and minimize cost, weight, and volume with underlining constraints. In the systems’ design and analysis phase, uncertainties can occur from various sources, such as manufacturing variability, environmental conditions, user behavior, etc. To deal with this, we present a generalization of the traditional MORRAP under multiple empirical and ambiguous circumstances, named interval type-2 fuzzy multiobjective reliability redundancy allocation problem (IT2FMORRAP). The newly formulated IT2FMORRAP considers optimizing goals as reliability, cost, and weight for a series-parallel system with interval type-2 fuzzy number. The mathematical formulation is established under which the proposed IT2FMORRAP model reduces to T1FMORRAP (type-1 fuzzy MORRAP), IVMORRAP (interval-valued MORRAP), and classical MORRAP. An Enhanced Karnik-Mendel and NSGA-II algorithm-based solving strategy is developed for the proposed IT2FMORRAP. The real-world dataset is considered to demonstrate the efficacy of the solution method for the proposed problem. A K-mean clustering technique identifies the best solution sets from the knee region of the generated Pareto fronts. An experimental study on commonly used performance metrics reveals that IT2FMORRAP performs significantly better than T1FMORRAP and crisp MORRAP. Further, the statistical analysis also confirms the hypothesis established in the empirical research. Finally, a comparative performance study has been conducted with notable state-of-the-art papers from the literature to encounter an appropriate establishment for the proposed work in the domain.https://ieeexplore.ieee.org/document/10052664/Multi-objective reliability optimizationtype-2 fuzzy reliabilitytype-2 fuzzy costtype-2 fuzzy weightNSGA-IIk-mean clustering |
| spellingShingle | Zubair Ashraf Mohammad Shahid Faisal Ahamd Mohammad Sajid Ketan Kotecha Shruti Patil A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties IEEE Access Multi-objective reliability optimization type-2 fuzzy reliability type-2 fuzzy cost type-2 fuzzy weight NSGA-II k-mean clustering |
| title | A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties |
| title_full | A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties |
| title_fullStr | A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties |
| title_full_unstemmed | A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties |
| title_short | A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties |
| title_sort | generalized multiobjective reliability redundancy allocation with uncertainties |
| topic | Multi-objective reliability optimization type-2 fuzzy reliability type-2 fuzzy cost type-2 fuzzy weight NSGA-II k-mean clustering |
| url | https://ieeexplore.ieee.org/document/10052664/ |
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