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Interval type-2 fuzzy modelling and stochastic search for real-world inventory management

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Abstract

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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Acknowledgments

The research reported here has been funded by the Technology Strategy Board (Grant No. H0254E).

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Correspondence to Simon Miller.

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Miller, S., Gongora, M., Garibaldi, J. et al. Interval type-2 fuzzy modelling and stochastic search for real-world inventory management. Soft Comput 16, 1447–1459 (2012). https://doi.org/10.1007/s00500-012-0848-y

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