Interval type-2 fuzzy modelling and stochastic search for real-world inventory management
Miller, Simon and Gongora, Mario and 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
Official URL: http://dx.doi.org/10.1007/s00500-012-0848-y
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.
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