Dynamics Analysis and Fractional-Order Approximate Entropy of Nonlinear Inventory Management Systems

Lei, Tengfei; Li, Rita Yi Man; Fu, Haiyan

doi:10.1155/2021/5516703

Cited by 15 publications

(10 citation statements)

References 35 publications

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“…To reduce the dependence on the accuracy of market demand forecasting and improve the efficiency of supply chain inventory management, it is necessary to improve inventory management efficiency to adapt to the changes in market demand. Besides, it is essential to use management methods to compensate for many negative impacts of market uncertainty [ 6 ]. In this case, the upstream and downstream enterprises of the supply chain must create a constant speed supply chain based on the network platform to reduce the inventory cost of the supply chain and meet the needs of customers in real time.…”

Section: Introductionmentioning

confidence: 99%

Construction and optimization of inventory management system via cloud-edge collaborative computing in supply chain environment in the Internet of Things era

Ran¹

2021

PLoS ONE

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The present work aims to strengthen the core competitiveness of industrial enterprises in the supply chain environment, and enhance the efficiency of inventory management and the utilization rate of inventory resources. First, an analysis is performed on the supply and demand relationship between suppliers and manufacturers in the supply chain environment and the production mode of intelligent plant based on cloud manufacturing. It is found that the efficient management of spare parts inventory can effectively reduce costs and improve service levels. On this basis, different prediction methods are proposed for different data types of spare parts demand, which are all verified. Finally, the inventory management system based on cloud-edge collaborative computing is constructed, and the genetic algorithm is selected as a comparison to validate the performance of the system reported here. The experimental results indicate that prediction method based on weighted summation of eigenvalues and fitting proposed here has the smallest error and the best fitting effect in the demand prediction of machine spare parts, and the minimum error after fitting is only 2.2%. Besides, the spare parts demand prediction method can well complete the prediction in the face of three different types of time series of spare parts demand data, and the relative error of prediction is maintained at about 10%. This prediction system can meet the basic requirements of spare parts demand prediction and achieve higher prediction accuracy than the periodic prediction method. Moreover, the inventory management system based on cloud-edge collaborative computing has shorter processing time, higher efficiency, better stability, and better overall performance than genetic algorithm. The research results provide reference and ideas for the application of edge computing in inventory management, which have certain reference significance and application value.

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Section: Introductionmentioning

confidence: 99%

Construction and optimization of inventory management system via cloud-edge collaborative computing in supply chain environment in the Internet of Things era

Ran¹

2021

PLoS ONE

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“…tokenisation [131], chatbots [132,133]; 3. Numerical data handling and analysis: scheduling [134,135] and planning [136], data analytics [137,138], forecasting [139], and inventory management [140].…”

Section: Automatic Machine Learning (Automl)mentioning

confidence: 99%

Predicting Carpark Prices Indices in Hong Kong Using AutoML

Li¹,

Song²,

Li³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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The aims of this study were threefold: 1) study the research gap in carpark and price index via big data and natural language processing, 2) examine the research gap of carpark indices, and 3) construct carpark price indices via repeat sales methods and predict carpark indices via the AutoML. By researching the keyword "carpark" in Google Scholar, the largest electronic academic database that covers Web of Science and Scopus indexed articles, this study obtained 999 articles and book chapters from 1910 to 2019. It confirmed that most carpark research threw light on multi-storey carparks, management and ventilation systems, and reinforced concrete carparks. The most common research method was case studies. Regarding price index research, many previous studies focused on consumer, stock, press and futures, with many keywords being related to finance and economics. These indicated that there is no research predicting carpark price indices based on an AutoML approach. This study constructed repeat sales indices for 18 districts in Hong Kong by using 34,562 carpark transaction records from December 2009 to June 2019. Wanchai's carpark price was about four times that of Yuen Long's carpark price, indicating the considerable carpark price differences in Hong Kong. This research evidenced the features that affected the carpark price indices models most: gold price ranked the first in all 19 models; oil price or Link stock price ranked second depending on the district, and carpark affordability ranked third.

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“…The ultimate goal of logistics is to minimize costs such as inventory expenses. Lei et al [5] simplified a three-dimensional discrete system into a two-dimensional discrete system for the discrete inventory management model and analyzed the nonlinear characteristics of the inventory management model using fractional complexity. Many professional scholars have studied this model [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Dynamics and Complexity Analysis of Fractional-Order Inventory Management System Model

Lei,

Li,

Deeprasert

et al. 2024

Fractal Fract

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To accurately depict inventory management over time, this paper introduces a fractional inventory management model that builds upon the existing classical inventory management framework. According to the definition of fractional difference equation, the numerical solution and phase diagram of an inventory management system are obtained by MATLAB simulation. The influence of parameters on the nonlinear behavior of the system is analyzed by a bifurcation diagram and largest Lyapunov exponent (LLE). Combined with the related indexes of time series, the complex characteristics of a quantization system are analyzed using spectral entropy and C0. This study concluded that the changing law of system complexity is consistent with the LLE of the system. By analyzing the influence of order on the system, it is found that the inventory changes will be periodic in some areas when the system is fractional, which is close to the actual conditions of the company’s inventory situation. The research results of this paper provide useful information for inventory managers to implement inventory and facility management strategies.

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Dynamics Analysis and Fractional-Order Approximate Entropy of Nonlinear Inventory Management Systems

Cited by 15 publications

References 35 publications

Construction and optimization of inventory management system via cloud-edge collaborative computing in supply chain environment in the Internet of Things era

Construction and optimization of inventory management system via cloud-edge collaborative computing in supply chain environment in the Internet of Things era

Predicting Carpark Prices Indices in Hong Kong Using AutoML

Dynamics and Complexity Analysis of Fractional-Order Inventory Management System Model

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