A robust inventory management in dynamic supply chains using an adaptive model-free control

被引:1
|
作者
Nya, Danielle Nyakam [1 ]
Abouaissa, Hassane [1 ]
机构
[1] Univ Artois, UR 3926, Lab Genie Informat & Automat Artois LGI2A, Technoparc Futura, F-62400 Bethune, France
关键词
Supply chain management; Inventory control; Model-free control; Time series; Forecasting; Algebraic techniques; Bullwhip effect; PREDICTIVE CONTROL; CONTROL STRATEGY; POLICIES; SYSTEMS; DESIGN;
D O I
10.1016/j.compchemeng.2023.108434
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
As a complex and nonlinear systems characterized by inherent delays, supply chains call for more robust and efficient strategies for their dynamic management. Given the inherent modeling challenges that often fail to capture their dynamic behavior, this paper examines the application of model-free control, as introduced by Fliess and Join, to address supply chain management (SCM) issues. The proposed control framework integrates the principles of model-free control, further enriched by recent advancements in time series analysis for delay compensation and customer demand forecasting. The primary objective, in addition to ensuring effective supply chain control, is to mitigate the intriguing bullwhip effect, where the system model is assumed unknown, and the delay is constant yet unknown. To substantiate this approach's effectiveness, we present several convincing computer simulations using real-world examples and compare the results with the internal model control strategy.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] Dynamic balancing of inventory in supply chains
    Agrawal, V
    Chao, XL
    Seshadri, S
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2004, 159 (02) : 296 - 317
  • [42] Adaptive inventory control models for supply chain management
    C.O. Kim
    J. Jun
    J.K. Baek
    R.L. Smith
    Y.D. Kim
    The International Journal of Advanced Manufacturing Technology, 2005, 26 : 1184 - 1192
  • [43] Adaptive inventory control models for supply chain management
    Kim, CO
    Jun, J
    Baek, JK
    Smith, RL
    Kim, YD
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2005, 26 (9-10): : 1184 - 1192
  • [44] Comparison of Adaptive and Model-Free Methods for Dynamic Measurement
    Markovsky, Ivan
    IEEE SIGNAL PROCESSING LETTERS, 2015, 22 (08) : 1094 - 1102
  • [45] Hierarchical Dynamic Power Management Using Model-Free Reinforcement Learning
    Wang, Yanzhi
    Triki, Maryam
    Lin, Xue
    Ammari, Ahmed C.
    Pedram, Massoud
    PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL SYMPOSIUM ON QUALITY ELECTRONIC DESIGN (ISQED 2013), 2013, : 170 - 177
  • [46] Model-free Adaptive Hysteresis for Dynamic Bandwidth Reservation
    Akar, Nail
    PROCEEDINGS OF MASCOTS '07: 15TH INTERNATIONAL SYMPOSIUM ON MODELING, ANALYSIS, AND SIMULATION OF COMPUTER AND TELECOMMUNICATION SYSTEMS, 2007, : 331 - 336
  • [47] Model-free adaptive dynamic programming for unknown systems
    Abu-Khalaf, Murad
    Lewis, Frank L.
    Al-Tamimi, Asma
    Vrabie, Draguna
    ICCSE'2006: PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION: ADVANCED COMPUTER TECHNOLOGY, NEW EDUCATION, 2006, : 105 - 114
  • [48] A model-free fuzzy adaptive trajectory tracking control algorithm based on dynamic surface control
    Tong, Mingsi
    Lin, Weiyang
    Huo, Xiang
    Jin, Zishu
    Miao, Chengzong
    INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2020, 17 (01)
  • [49] Model-free control of a quadrotor using adaptive proportional derivative-sliding mode control and robust integral of the signum of the error
    Li, Zhi
    Ma, Xin
    Li, Yibin
    INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2018, 15 (05):
  • [50] A Model-Free Robust Control Approach for Robot Manipulator
    Izadbakhsh, A.
    Fateh, M. M.
    PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 23, 2007, 23 : 205 - 210