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Sliding mode control of periodic review perishable inventories with multiple suppliers and transportation losses

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The purpose of this paper is to develop robust and computationally efficient supply chain management strategy ensuring fast reaction to the demand variations for periodic review perishable inventory systems. For that purpose, we apply a sliding mode approach and we propose a new discrete time warehouse management strategy. The strategy employs the sliding hyperplane appropriately designed to ensure a dead-beat performance of the closed loop system. Our strategy not only explicitly takes into account decay of goods stored in the warehouse (perishing inventories) but it also accounts for transportation losses which take place on the way from suppliers to the warehouse. The proposed strategy ensures full customers’ demand satisfaction, minimizes the on-hand inventory volume and prevents from exceeding the warehouse capacity. This reflects the need of simultaneous minimization of the lost sales costs and inventory holding costs. Furthermore, the strategy ensures that the ordered quantities of goods are always non-negative and upper bounded. These favourable properties of the proposed strategy are formally stated as a lemma and three theorems and proved in the paper.
Rocznik
Strony
885--892
Opis fizyczny
Bibliogr. 38 poz., rys., tab., wykr.
Twórcy
  • Institute of Automatic Control, Lodz University of Technology, 18/22 Stefanowskiego St., 90-924 Łodź, Poland
  • Institute of Automatic Control, Lodz University of Technology, 18/22 Stefanowskiego St., 90-924 Łodź, Poland
Bibliografia
  • [1] H. Sarimveis, P. Patrinos, C. D. Tarantilis, and C. T. Kiranoudis, “Dynamic modeling and control of supply chain systems: a review”, Computers and Operations Research 35 (11), 3530-3561 (2008).
  • [2] C. Riddalls, S. Bennett, and N. Tipi, “Modelling the dynamics of supply chains”, Int. J. Systems Science 31 (8), 969-976 (2000).
  • [3] I. Karaesmen, A. Scheller-Wolf, and B. Deniz, “Managing perishable and aging inventories: review and future research directions”, in Handbook of Production Planning, eds. K. Kempf, P. Keskinoca, and R. Uzsoy, Kluwer, Dordrecht, 2008.
  • [4] M. Boccadoro, F. Martinelli, and P. Valigi, “Supply chain management by H-infinity control”, IEEE Trans. on Automation Science and Engineering 5 (4), 703-707 (2008).
  • [5] K. Hoberg, J. R. Bradley, and U. W. Thonemann, “Analyzing the effect of the inventory policy on order and inventory variability with linear control theory”, Eur. J. Operations Research 176 (3), 1620-1642 (2007).
  • [6] K. Subramanian, “Integration of control theory and scheduling methods for supply chain management”, PhD Thesis, University of Wisconsin-Madison, Madison, 2013.
  • [7] H. A. Simon, “On the application of servomechanism theory in the study of production control”, Econometrica 20 (2), 247-268 (1952).
  • [8] H.J. Vassian, Application of Discrete Variable Servo Theory to Inventory Control, Arthur D. Little, Inc., Cambridge, 1954.
  • [9] J. Forrester, “Industrial dynamics, a major breakthrough for decision makers”, Harvard Business Review 36 (4), 37-66 (1958).
  • [10] D.R. Towill, “Dynamic analysis of an inventory and order based production control system”, Int. J. Production Research 20 (6), 671-687 (1982).
  • [11] J. Dejonckheere, S.M. Disney, M.R. Lambrecht, and D.R. Towill, “The impact of information on the bullwhip effect in supply chains: a control engineering perspective”, Eur. J. Operational Research 153 (3), 727-750 (2004).
  • [12] G. Gaalman and S.M. Disney, “State space investigation of the bullwhip problem with ARMA(1,1) demand processes”, Int. J. Production Economics 104 (2), 327-339 (2006).
  • [13] C.S. Lalwani, S.M. Disney, and D.R. Towill, “Controllable, observable and stable state space representations of a generalized order-up-to policy”, Int. J. Production Economics 101 (1), 172-184 (2006).
  • [14] A. Potter, D.R. Towill, T. Bohme, and S.M. Disney, “The influence of multi-product production strategy on factory induced bullwhip”, Int. J. Production Research 47 (20), 5739-5759 (2009).
  • [15] L. Zhou, S.M. Disney, and D.R. Towill, “A pragmatic approach to the design of bullwhip controllers”, Int. J. Production Economics 128 (2), 556-568 (2010).
  • [16] G. Gaalman, “Bullwhip reduction for ARMA demand: the proportional order-up-to policy versus the full-state-feedback policy”, Automatica 42 (8), 1283-1290 (2006).
  • [17] E. Aggelogiannaki, P. Doganis, and H. Sarimveis, “An adaptive model predictive control configuration for productioninventory systems”, Int. J. Production Economics 114 (1), 165-178 (2008).
  • [18] X. Li, and T.E. Marlin, “Robust supply chain performance via Model Predictive Control”, Computers & Chemical Engineering 33 (12), 2134-2143 (2009).
  • [19] W. Wang, D.E. Rivera, and K.G. Kempf, “Model predictive control strategies for supply chain management in semiconductor manufacturing”, Int. J. Production Economics 107 (1), 56-77 (2007).
  • [20] E. K. Boukas, P. Shi, and R.K. Agarwal, “An application of robust technique to manufacturing systems with uncertain processing time”, Optimal Control Applications and Methods 21 (6), 257-268 (2000).
  • [21] E. Aggelogiannaki and H. Sarimveis, “Design of a novel adaptive inventory control system based on the online identification of lead time”, Int. J. Production Economics 114 (2), 781-792 (2008).
  • [22] Y. Feng, S. Chen, A. Kumar, and B. Lin, “Solving singleproduct economic lot-sizing problem with non-increasing setup cost, constant capacity and convex inventory cost in O(N log N) time”, Computers and Operations Research 38 (4), 717-722 (2011).
  • [23] S.H. Pasandideh, S.T. Niaki, and A.R. Nia, “A genetic algorithm for vendor managed inventory control system of multiproduct multi-constraint economic order quantity model”, Expert Systems with Applications 38 (3), 2708-2716 (2011).
  • [24] S.C. Liu and J.R. Chen, “A heuristic method for the inventory routing and pricing problem in a supply chain”, Expert Systems with Applications 38 (3), 1447-1456 (2011).
  • [25] P. K¨ochel and U. Niel¨ander, “Simulation-based optimisation of multi-echelon inventory systems”, Int. J. Production Economics 93-94 (1), 505-513 (2005).
  • [26] P. Ignaciuk and A. Bartoszewicz, “Linear-quadratic optimal control strategy for periodic-review inventory systems”, Automatica 46 (12), 1982-1993 (2010).
  • [27] P. Ignaciuk and A. Bartoszewicz, “LQ optimal sliding mode supply policy for periodic inventory systems”, IEEE Trans. on Automatic Control 55 (1), 269-274 (2010).
  • [28] P. Ignaciuk and A. Bartoszewicz, “Linear-quadratic optimal control of periodic-review perishable inventory systems”, IEEE Trans. on Control Systems Technology 20 (5), 1400-1407 (2012).
  • [29] P. Ignaciuk and A. Bartoszewicz, “LQ optimal sliding-mode supply policy for periodic-review perishable inventory systems”, J. Franklin Institute, 349 (4), 1561-1582 (2012).
  • [30] P. Ignaciuk and A. Bartoszewicz, “Dead-beat and reachinglaw- based sliding-mode control of perishable inventory systems”, Bull. Pol. Ac.: Tech. 59 (1), 39-49 (2011).
  • [31] V. Utkin and S. V. Drakunow, “On discrete-time sliding mode control”, IFAC Conf. on Nonlinear Control 1, 484-489 (1989).
  • [32] K. Furuta, “Sliding mode control of a discrete system”, Systems and Control Letters 14 (2), 145-152 (1990).
  • [33] W. Gao, Y. Wang, and A. Homaifa, “Discrete-time variable structure control system”, IEEE Trans. on Industrial Electronics 42 (2), 117-122 (1995).
  • [34] A. Bartoszewicz, “Remarks on ‘Discrete-time variable structure control systems”’, IEEE Trans. on Industrial Electronics 43 (1), 235-238 (1996).
  • [35] G. Golo and C. Milosavljević, “Robust discrete-time chattering free sliding mode control”, Systems and Control Letters 41 (1), 19-28 (2000).
  • [36] B. Bandyopadhyay and S. Janardhanan, Discrete-time Sliding Mode Control: a Multirate Output Feedback Approach LNCIS 323, Springer-Verlag, Berlin, 2006.
  • [37] C. Milosavljević, B. Peruniˇcić-Draˇzenović, B. Veselić, and D. Mitić, “Sampled data quasi-sliding mode control strategies”, IEEE Int. Conf. on Industrial Technology 1, 2640-2645 (2006).
  • [38] X. Yu, B. Wang, and X. Li, “Computer-controlled variable structure systems: the state of the art”, IEEE Trans. on Industrial Informatics 8 (2), 197-205 (2012).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e9882b8d-840b-40d8-b0a3-aed0d1475bc0
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