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 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 beneSimon Miller Horizon Digital Economy Research / Intelligent Modelling and Analysis, University of Nottingham, Nottingham, UK Tel.: +44 (0)115 8232556 E-mail: [email protected] Mario Gongora · Robert John Centre for Computational Intelligence, De Montfort University, Leicester, UK E-mail: [email protected],[email protected] Jon Garibaldi Intelligent Modelling and Analysis, University of Nottingham, Nottingham, UK E-mail: [email protected] fits that a Type-2 model offers, can make it preferable to a corresponding Type-1 system.