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A State‐Feedback Approach to Inventory Control: Analytical and Empirical Studies
Author(s) -
Zhao Yingxue,
Zhao Chuan,
He Mingke,
Yang Changchun
Publication year - 2016
Publication title -
production and operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.279
H-Index - 110
eISSN - 1937-5956
pISSN - 1059-1478
DOI - 10.1111/poms.12522
Subject(s) - computer science , state (computer science) , control (management) , feedback control , inventory control , compensation (psychology) , reduction (mathematics) , order (exchange) , control theory (sociology) , process (computing) , inventory theory , empirical research , operations research , control engineering , economics , mathematics , statistics , engineering , artificial intelligence , psychology , geometry , finance , algorithm , psychoanalysis , operating system
By applying the state feedback principle of control theory, this study develops a state‐feedback model that is capable of self‐compensation and self‐adjustment for inventory control. To be specific, under the state‐feedback model, deviation between material order quantity and actual shipment can be dynamically adjusted in response to the actual shipment with the pole‐placement state‐feedback mechanism. As a result of this merit, the state‐feedback model can ensure a more accurate order in each step of the inventory control process and thereby attain a more effective inventory control, particularly, a significant reduction of the inventory cost. In addition to analytical research, empirical studies are also conducted for the analytical model by using data collected from the industry. The empirical results show that the state‐feedback model can attain a significant improvement for inventory control and the effectiveness and applicability of the state‐feedback model can be well empirically tested.