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

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Tengfei Lei ◽  
Rita Yi Man Li ◽  
Haiyan Fu
Keyword(s):  
Lyapunov Exponent ◽  
Inventory Management ◽  
Approximate Entropy ◽  
Human Action ◽  
Management Model ◽  
Management Systems ◽  
Largest Lyapunov Exponent ◽  
Complex Nonlinear Systems ◽  
Definition Of ◽  
Special Circumstances

Inventory management is complex nonlinear systems that are affected by various external factors, including course human action and policy. We study the inventory management model under special circumstances and analyse the equilibrium point of the system. The dynamics of the system is analysed by means of the eigenvalue trajectory, bifurcations, chaotic attractor, and largest Lyapunov exponent diagram. At the same time, according to the definition of fractional calculus, the fractional approximate entropy is used to analyse the system, and the results are consistent with those of the largest Lyapunov exponent diagram, which shows the effectiveness of this method.

Research of Extracting Information about Reservoir Logging Signals Based on Chaos Characteristics

2013 ◽  
Vol 380-384 ◽  
pp. 3742-3745
Author(s):  
Chun Yan Nie ◽  
Rui Li ◽  
Wan Li Zhang
Keyword(s):  
Lyapunov Exponent ◽  
Correlation Dimension ◽  
Approximate Entropy ◽  
Water Layer ◽  
Time Correlation ◽  
Largest Lyapunov Exponent ◽  
Characteristic Parameters ◽  
Chaotic Characteristic ◽  
Oil Water

The mechanism of logging signals generating was researched. In the same time, correlation dimension, largest Lyapunov exponent and approximate entropy of chaotic characteristics were extracted. On this basis, chaotic characteristic parameters were applied in processing, analysis and interpretation, try to find chaotic characteristics of different of reservoirs for example oil, water layer and the dry layer. The results showed that chaos characteristics in different reservoir is different, therefore, we can distinguish the different natures of reservoirs by extracting chaos characteristics.

DIGITAL ECONOMY AND GLOBALIZATION: THE IMPORTANCE OF DIGITAL ENTREPRENEURSHIP DEVELOPMENT

2020 ◽  
Vol 6 (3) ◽  
pp. 17-20
Author(s):  
Farxod Tursunov ◽  
Keyword(s):  
Business Models ◽  
Digital Economy ◽  
Management Systems ◽  
Entrepreneurship Development ◽  
New Business ◽  
Definition Of ◽  
Digital Enterprise ◽  
New Business Models ◽  
Digital Entrepreneurship

The article discusses the role of the digital economy in the development of the country, how it becomes the basis of the economy, new business models and management systems. The opinion of scientistsis analyzed, a definition of a digital enterprise is given

Inventory optimization considering the vehicle capacity and specifics of cash flows at rental storage sites

2020 ◽  
pp. 77-90
Author(s):  
V.D. Gerami ◽  
I.G. Shidlovskii
Keyword(s):  
Supply Chain ◽  
Inventory Management ◽  
Sufficient Conditions ◽  
Cash Flows ◽  
Management Systems ◽  
Cargo Capacity ◽  
Special Modification ◽  
The Cost ◽  
Necessary And Sufficient ◽  
Vehicle Capacity

The article presents a special modification of the EOQ formula and its application to the accounting of the cargo capacity factor for the relevant procedures for optimizing deliveries when renting storage facilities. The specified development will allow managers to take into account the following process specifics in the format of a simulated supply chain when managing inventory. First of all, it will allow considering the most important factor of cargo capacity when optimizing stocks. Moreover, this formula will make it possible to find the optimal strategy for the supply of goods if, also, it is necessary to take into account the combined effect of several factors necessary for practice, which will undoubtedly affect decision-making procedures. Here we are talking about the need for additional consideration of the following essential attributes of the simulated cash flow of the supply chain: 1) time value of money; 2) deferral of payment of the cost of the order; 3) pre-agreed allowable delays in the receipt of revenue from goods sold. Developed analysis and optimization procedures have been implemented to models of this type that are interesting and important for a business. This — inventory management systems, the format of which is related to the special concept of efficient supply. We are talking about models where the presence of the specified delays for the outgoing cash flows allows you to pay for the order and the corresponding costs of the supply chain from the corresponding revenue on the re-order interval. Accordingly, the necessary and sufficient conditions are established based on which managers will be able to identify models of the specified type. The purpose of the article is to draw the attention of managers to real opportunities to improve the efficiency of inventory management systems by taking into account these factors for a simulated supply chain.

EFFECTS OF TREND AND PERIODICITY ON THE CORRELATION DIMENSION AND THE LYAPUNOV EXPONENTS

2008 ◽  
Vol 18 (12) ◽  
pp. 3679-3687 ◽  
Author(s):  
AYDIN A. CECEN ◽  
CAHIT ERKAL
Keyword(s):  
Time Series ◽  
Lyapunov Exponent ◽  
Lyapunov Exponents ◽  
Correlation Dimension ◽  
Time Series Data ◽  
Logistic Map ◽  
Model Identification ◽  
Series Data ◽  
Largest Lyapunov Exponent ◽  
The Impact

We present a critical remark on the pitfalls of calculating the correlation dimension and the largest Lyapunov exponent from time series data when trend and periodicity exist. We consider a special case where a time series Zi can be expressed as the sum of two subsystems so that Zi = Xi + Yi and at least one of the subsystems is deterministic. We show that if the trend and periodicity are not properly removed, correlation dimension and Lyapunov exponent estimations yield misleading results, which can severely compromise the results of diagnostic tests and model identification. We also establish an analytic relationship between the largest Lyapunov exponents of the subsystems and that of the whole system. In addition, the impact of a periodic parameter perturbation on the Lyapunov exponent for the logistic map and the Lorenz system is discussed.

The Lyapunov Exponent Variance of an Electronic Manufacturing Enterprise’s Daily Qualified Rate Time Series by Improved Small Data Sets Approach

2012 ◽  
Vol 197 ◽  
pp. 271-277
Author(s):  
Zhu Ping Gong
Keyword(s):  
Time Series ◽  
Lyapunov Exponent ◽  
Chaotic Time Series ◽  
Quality System ◽  
Quality Level ◽  
Largest Lyapunov Exponent ◽  
Small Data ◽  
Data Set ◽  
Electronic Manufacturing ◽  
Small Data Set

Small data set approach is used for the estimation of Largest Lyapunov Exponent (LLE). Primarily, the mean period drawback of Small data set was corrected. On this base, the LLEs of daily qualified rate time series of HZ, an electronic manufacturing enterprise, were estimated and all positive LLEs were taken which indicate that this time series is a chaotic time series and the corresponding produce process is a chaotic process. The variance of the LLEs revealed the struggle between the divergence nature of quality system and quality control effort. LLEs showed sharp increase in getting worse quality level coincide with the company shutdown. HZ’s daily qualified rate, a chaotic time series, shows us the predictable nature of quality system in a short-run.

Study of Rehabilitation of Injured Knee Joint Applying Chaotic Theory in Human Body Motion

2007 ◽  
Vol 342-343 ◽  
pp. 581-584
Author(s):  
Byung Young Moon ◽  
Kwon Son ◽  
Jung Hong Park
Keyword(s):  
Time Series ◽  
Lyapunov Exponent ◽  
Angular Displacement ◽  
Three Dimensional ◽  
Gait Pattern ◽  
Body Motion ◽  
Largest Lyapunov Exponent ◽  
Chaos Analysis ◽  
Nonlinear Technique ◽  
Injured Knee

Gait analysis is essential to identify accurate cause and knee condition from patients who display abnormal walking. Traditional linear tools can, however, mask the true structure of motor variability, since biomechanical data from a few strides during the gait have limitation to understanding the system. Therefore, it is necessary to propose a more precise dynamic method. The chaos analysis, a nonlinear technique, focuses on understanding how variations in the gait pattern change over time. Healthy eight subjects walked on a treadmill for 100 seconds at 60 Hz. Three dimensional walking kinematic data were obtained using two cameras and KWON3D motion analyzer. The largest Lyapunov exponent from the measured knee angular displacement time series was calculated to quantify local stability. This study quantified the variability present in time series generated from gait parameter via chaos analysis. Gait pattern is found to be chaotic. The proposed Lyapunov exponent can be used in rehabilitation and diagnosis of recoverable patients.

A Very Simple Method to Calculate the (Positive) Largest Lyapunov Exponent Using Interval Extensions

2016 ◽  
Vol 26 (13) ◽  
pp. 1650226 ◽  
Author(s):  
Eduardo M. A. M. Mendes ◽  
Erivelton G. Nepomuceno
Keyword(s):  
Lyapunov Exponent ◽  
Lower Bound ◽  
Equations Of Motion ◽  
Original System ◽  
Glass System ◽  
Largest Lyapunov Exponent ◽  
Simple Method ◽  
Interval Extensions

In this letter, a very simple method to calculate the positive Largest Lyapunov Exponent (LLE) based on the concept of interval extensions and using the original equations of motion is presented. The exponent is estimated from the slope of the line derived from the lower bound error when considering two interval extensions of the original system. It is shown that the algorithm is robust, fast and easy to implement and can be considered as alternative to other algorithms available in the literature. The method has been successfully tested in five well-known systems: Logistic, Hénon, Lorenz and Rössler equations and the Mackey–Glass system.

scholarly journals Diagnostic of cardio-vascular disease with help of largest Lyapunov exponent of RR-sequences

2000 ◽  
Vol 11 (5) ◽  
pp. 807-814 ◽  
Author(s):  
Alexey N Pavlov ◽  
Natalia B Janson ◽  
Vadim S Anishchenko ◽  
Vladimir I Gridnev ◽  
Pavel Ya Dovgalevsky
Keyword(s):  
Lyapunov Exponent ◽  
Vascular Disease ◽  
Largest Lyapunov Exponent ◽  
Cardio Vascular Disease ◽  
Cardio Vascular

APPLICATION OF PERIODIC REVIEW INVENTORIES MODEL IN A TYPICAL MEXICAN FOOD COMPANY

2021 ◽  
Vol 8 (1) ◽  
pp. 27-36
Author(s):  
Ramsés Cabrera-Gala ◽  
Luis Carreón-Nava ◽  
Hugo Valencia-Cuevas ◽  
León Rivera-Sosa
Keyword(s):  
Inventory Management ◽  
Management Model ◽  
Periodic Review ◽  
Food Company ◽  
Periodic Model ◽  
Santa Monica ◽  
Typical Food ◽  
The One ◽  
The City ◽  
Optimal Quantity

The Mexican family companies must face the challenges of market volatility with greater recurrence, forcing them to use effective tools and models for the proper management of their organizations and inherent activities, such as inventory management. Therefore, this research was carried out at “Moles Santa Monica”, a typical food company located in the city of Puebla, Mexico. This enterprise has reflected a high variability in the administration of its inventories, with a Coefficient of Variation (CV) greater than 0.2 in most of their portfolio products. In this way, the objective of this study was to propose an inventory management model that might reduce the shortages and overstock, and also; improves its performance and profitability when it is managed. The applied methods were Pareto and ABC model to choose correctly the best seller company products. The inventory management model chosen was the periodic review (R, S) as well, for being the most effective and the one that best suited the circumstances of the company in question. Three of the portfolio products were studied (MPP10, MPC10 and COP10) due to they are the most representative in incomes and valuables for the company managers. The results allowed us to propose the review periodic model (R), the optimal quantity of units to produce (Q), the safety stock (Ss) and the maximum inventory (S) for each product. We conclude that this model will help the company to face the uncertainty of the demand. Finally, we include limitations and future studies.

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