Interval type-2 fuzzy modelling and stochastic search for real-world inventory management
Real-world systems present a variety of challenges to the modeller, not least of which is the problem of uncertainty inherent in their operation. In this research, an interval type-2 fuzzy model is applied to a real-world problem, the goal being to discover a suitable optimisation configuration to e...
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| Format: | Article |
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Springer-Verlag
2012
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| Online Access: | https://eprints.nottingham.ac.uk/27774/ |
| _version_ | 1848793435337654272 |
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| author | Miller, Simon Gongora, Mario Garibaldi, Jon John, Robert |
| author_facet | Miller, Simon Gongora, Mario Garibaldi, Jon John, Robert |
| author_sort | Miller, Simon |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Real-world systems present a variety of challenges to the modeller, not least of which is the problem of uncertainty inherent in their operation. In this research, an interval type-2 fuzzy model is applied to a real-world problem, the goal being to discover a suitable optimisation configuration to enable a search for an inventory plan using the model. To this end, a series of simulated annealing configurations and the interval type-2 fuzzy model were used to search for appropriate inventory plans for a large-scale real-world problem. A further set of tests were conducted in which the performance of the interval type-2 fuzzy model was compared with a corresponding type-1 fuzzy model. In these tests the results were inconclusive, though, as will be discussed there are many ways in which type-2 fuzzy logic can be exploited to demonstrate its advantages over a type-1 approach. To conclude, in this research we have shown that a combination of interval type-2 fuzzy logic and simulated annealing is a logical choice for inventory management modelling and inventory plan search, and propose that the benefits that a type-2 model offers, can make it preferable to a corresponding type-1 system. |
| first_indexed | 2025-11-14T19:00:15Z |
| format | Article |
| id | nottingham-27774 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:00:15Z |
| publishDate | 2012 |
| publisher | Springer-Verlag |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-277742020-05-04T20:22:40Z https://eprints.nottingham.ac.uk/27774/ Interval type-2 fuzzy modelling and stochastic search for real-world inventory management Miller, Simon Gongora, Mario Garibaldi, Jon John, Robert Real-world systems present a variety of challenges to the modeller, not least of which is the problem of uncertainty inherent in their operation. In this research, an interval type-2 fuzzy model is applied to a real-world problem, the goal being to discover a suitable optimisation configuration to enable a search for an inventory plan using the model. To this end, a series of simulated annealing configurations and the interval type-2 fuzzy model were used to search for appropriate inventory plans for a large-scale real-world problem. A further set of tests were conducted in which the performance of the interval type-2 fuzzy model was compared with a corresponding type-1 fuzzy model. In these tests the results were inconclusive, though, as will be discussed there are many ways in which type-2 fuzzy logic can be exploited to demonstrate its advantages over a type-1 approach. To conclude, in this research we have shown that a combination of interval type-2 fuzzy logic and simulated annealing is a logical choice for inventory management modelling and inventory plan search, and propose that the benefits that a type-2 model offers, can make it preferable to a corresponding type-1 system. Springer-Verlag 2012 Article PeerReviewed Miller, Simon, Gongora, Mario, Garibaldi, Jon and John, Robert (2012) Interval type-2 fuzzy modelling and stochastic search for real-world inventory management. Soft Computing, 16 (8). pp. 1447-1459. ISSN 1432-7643 Interval type-2 fuzzy logic; Real-world inventory management; Simulated annealing http://dx.doi.org/10.1007/s00500-012-0848-y doi:10.1007/s00500-012-0848-y doi:10.1007/s00500-012-0848-y |
| spellingShingle | Interval type-2 fuzzy logic; Real-world inventory management; Simulated annealing Miller, Simon Gongora, Mario Garibaldi, Jon John, Robert Interval type-2 fuzzy modelling and stochastic search for real-world inventory management |
| title | Interval type-2 fuzzy modelling and stochastic search for real-world inventory management |
| title_full | Interval type-2 fuzzy modelling and stochastic search for real-world inventory management |
| title_fullStr | Interval type-2 fuzzy modelling and stochastic search for real-world inventory management |
| title_full_unstemmed | Interval type-2 fuzzy modelling and stochastic search for real-world inventory management |
| title_short | Interval type-2 fuzzy modelling and stochastic search for real-world inventory management |
| title_sort | interval type-2 fuzzy modelling and stochastic search for real-world inventory management |
| topic | Interval type-2 fuzzy logic; Real-world inventory management; Simulated annealing |
| url | https://eprints.nottingham.ac.uk/27774/ https://eprints.nottingham.ac.uk/27774/ https://eprints.nottingham.ac.uk/27774/ |