Switching DSM Control of Perishable Inventory Systems with Delayed Shipments and Uncertain Demand
In this chapter, the concept of discrete sliding modes (DSMs) is applied to design an efficient supply policy for a class of perturbed processes with delay – goods flow control in supply chain. In the considered systems, the stock used to satisfy the unknown, time-varying demand placed at a goods distribution center; is replenished with delay from a remote supply source. The order quantity is fixed, leaving the time between the consecutive orders as a decision variable, which perfectly suits the switching nature of input signals obtained in DSM control systems. It is shown that under the proposed nonlinear policy, the stock level does not exceed the assigned storage space. Moreover, it is also demonstrated that the stock is never entirely depleted, which guarantees full demand satisfaction and maximum service level.
KeywordsInventory System Slide Mode Control Order Quantity Switching Function Stock Level
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- 1.Bandyopadhyay, B., Janardhanan, S.: Discrete-time sliding mode control: a multirate output feedback approach. LNCIS, vol. 323. Springer, Heidelberg (2006)Google Scholar
- 2.Bandyopadhyay, B., Fulwani, D., Kim, K.S.: Sliding mode control using novel sliding surfaces. LNCIS, vol. 392. Springer, Heidelberg (2010)Google Scholar
- 13.Karaesmen, I., Scheller-Wolf, A., Deniz, B.: Managing perishable and aging inventories: review and future research directions,”. In: Kempf, K., Keskinocak, P., Uzsoy, R. (eds.) Handbook of Production Planning. Kluwer, Dordrecht (2008)Google Scholar
- 15.Milosavljević, Č., Peruničić-Draženovic, B., Veselić, B., Mitić, D.: Sampled data quasi-sliding mode control strategies. In: Proc. IEEE Int. Conf. Ind. Technol., pp. 2640–2645 (2006)Google Scholar
- 18.Rafaat, F.: Survey of literature on continuously deteriorating inventory models. J. Oper. Res. Soc. 42, 27–37 (1991)Google Scholar
- 21.Silver, E.A., Pyke, D.F., Peterson, R.: Inventory management and production planning and scheduling. John Wiley, Chichester (1998)Google Scholar