An Optimal Location-Allocation Model for Equipment Supporting System Based on Uncertainty Theory
Scientific support depot location and reasonable spare parts transportation are the keys to improving the support level of complex systems. The current equipment support system has the problems of chaotic warehouse layout and low efficiency of spare parts. The reliability and completeness of spare p...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/15/2/338 |
| _version_ | 1797618077786963968 |
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| author | Han Li Wenshu Xie Meilin Wen Shuyu Li Yi Yang Linhan Guo |
| author_facet | Han Li Wenshu Xie Meilin Wen Shuyu Li Yi Yang Linhan Guo |
| author_sort | Han Li |
| collection | DOAJ |
| description | Scientific support depot location and reasonable spare parts transportation are the keys to improving the support level of complex systems. The current equipment support system has the problems of chaotic warehouse layout and low efficiency of spare parts. The reliability and completeness of spare parts’ historical data are hard to believe. In order to deal with the cognitive uncertainty caused by the asymmetry of data, this paper adopts the uncertainty theory to optimize the depot location and transportation volume. Under the constraints of shortage rate, supply availability, average logistic delay time, and inventory limit, the uncertain chance-constrained model of equipment supporting depot is established. The optimization model is transformed into a deterministic model by using the inverse uncertainty distribution. The genetic algorithm is used to optimize the solution of this model. Finally, the practicability and operability of the model method are verified through the example analysis. |
| first_indexed | 2024-03-11T08:05:08Z |
| format | Article |
| id | doaj.art-a9bc5d05d2a5418eb7a8e0bcc61e624c |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-11T08:05:08Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-a9bc5d05d2a5418eb7a8e0bcc61e624c2023-11-16T23:31:59ZengMDPI AGSymmetry2073-89942023-01-0115233810.3390/sym15020338An Optimal Location-Allocation Model for Equipment Supporting System Based on Uncertainty TheoryHan Li0Wenshu Xie1Meilin Wen2Shuyu Li3Yi Yang4Linhan Guo5School of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaChina Academy of Launch Vehicle Technology, Beijing 100076, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaScientific support depot location and reasonable spare parts transportation are the keys to improving the support level of complex systems. The current equipment support system has the problems of chaotic warehouse layout and low efficiency of spare parts. The reliability and completeness of spare parts’ historical data are hard to believe. In order to deal with the cognitive uncertainty caused by the asymmetry of data, this paper adopts the uncertainty theory to optimize the depot location and transportation volume. Under the constraints of shortage rate, supply availability, average logistic delay time, and inventory limit, the uncertain chance-constrained model of equipment supporting depot is established. The optimization model is transformed into a deterministic model by using the inverse uncertainty distribution. The genetic algorithm is used to optimize the solution of this model. Finally, the practicability and operability of the model method are verified through the example analysis.https://www.mdpi.com/2073-8994/15/2/338equipment support systemlocation optimizationuncertainty theoryuncertain chance-constrained programming |
| spellingShingle | Han Li Wenshu Xie Meilin Wen Shuyu Li Yi Yang Linhan Guo An Optimal Location-Allocation Model for Equipment Supporting System Based on Uncertainty Theory Symmetry equipment support system location optimization uncertainty theory uncertain chance-constrained programming |
| title | An Optimal Location-Allocation Model for Equipment Supporting System Based on Uncertainty Theory |
| title_full | An Optimal Location-Allocation Model for Equipment Supporting System Based on Uncertainty Theory |
| title_fullStr | An Optimal Location-Allocation Model for Equipment Supporting System Based on Uncertainty Theory |
| title_full_unstemmed | An Optimal Location-Allocation Model for Equipment Supporting System Based on Uncertainty Theory |
| title_short | An Optimal Location-Allocation Model for Equipment Supporting System Based on Uncertainty Theory |
| title_sort | optimal location allocation model for equipment supporting system based on uncertainty theory |
| topic | equipment support system location optimization uncertainty theory uncertain chance-constrained programming |
| url | https://www.mdpi.com/2073-8994/15/2/338 |
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