Research on Supply Chain Stability Driven by Consumer’s Channel Preference Based on Complexity Theory

Contributors

Effect of noise and filtering on largest Lyapunov exponent of time series associated with human walking

Due to the important role of the vaccines in the prevention of global epidemics, this paper focuses on a vaccine transportation supply chain composed of one distributor and one retailer. Based on the assumption that the decision-maker does not make a decision instantaneously, we present a decision-making time-delay model. Firstly, we captured some sufficient conditions of delay-induced bifurcation for the model by regarding different combinations of the decision delay periods as the bifurcation parameters and analyzed how the speed of decision-making adjustment of distributor or retailer affects the critical point of system stability. Secondly, we made a numerical simulation on the model by using a two-dimensional bifurcation diagram, largest Lyapunov exponent, and entropy and chaotic attractor, respectively. Finally, we used two coordination methods to control chaos and compared them. The results show that when the decision delay exceeds a certain threshold, the system will lose stability or go into chaos. The precipitous speed of decision variable adjustment of the distributor or retailer will increase the entropy of the system and lead the system into a chaotic state. When the vaccine supply chain is in chaos, the effect of external control on chaos is better than that of internal control on chaos.

Although research on supply chain management has made many valuable contributions, there is a dearth of empirical evidence and theoretical reflection on the characteristics of supply chains that operate mainly in developing and emerging economies. The aim of this paper is to help to fill this gap by exploring how supply chain sustainability can be implemented and managed in these settings. An in-depth case study of the upstream oil and gas industry supply chain in Brazil was used to develop propositions about supply chains that operate in developing settings. Drawing from institutional theory, evolutionary theory, complexity theory, and from the organizational learning, innovation, and strategy literatures, this paper offers four key findings and contributions to the supply chain literature. First, it shows that becoming a sustainable supply chain is not a destination, but a journey, where trajectory and time matter. Given the evolutionary nature of supply chain sustainability trajectories, this paper highlights that supply chains learn and evolve just as organizations do. Second, this research indicates that, although globalization is a trend, natural resource-based supply chains are often more geographically bounded and susceptible to local social demands than other supply chains. Third, this paper extends the supply chain literature by arguing that supply chains face additional barriers to sustainability in developing and emerging economies, which contribute to a higher degree of complexity and uncertainty due to the existence of highly turbulent business environments and institutional voids. These factors in turn hinder supply chain learning and innovation, and reduce the slope of supply chains sustainability trajectories. Finally, this research contributes to the literature by claiming that, due to the highly complex and uncertain business environments, in these settings focal companies play an even more important role in managing the escalating ambiguity, stimulating supply chain learning, and promoting innovation towards supply chains enhanced sustainability performance.

The ability of the locomotor system to maintain continuous walking despite very small external or internal disturbances is called local dynamic stability (LDS). The importance of the LDS requires constantly working on different aspects of its assessment method which is based on the short-term largest Lyapunov exponent (LLE). A state space structure is a vital aspect of the LDS assessment because the algorithm of the LLE computation for experimental data requires a reconstruction of a state space trajectory. The gait kinematic data are usually one- or three-dimensional, which enables to construct a state space based on a uni- or multivariate time series. Furthermore, two variants of the short-term LLE are present in the literature which differ in length of a time span, over which the short-term LLE is computed. Both a state space structure and the consistency of the observations based on values of both short-term LLE variants were analyzed using time series representing the joint angles at ankle, knee, and hip joints. The short-term LLE was computed for individual joints in three state spaces constructed on the basis of either univariate or multivariate time series. Each state space revealed walkers' locally unstable behavior as well as its attenuation in the current stride. The corresponding conclusions made on the basis of both short-term LLE variants were consistent in ca. 59% of cases determined by a joint and a state space. Moreover, the authors present an algorithm for estimation of the embedding dimension in the case of a multivariate gait time series.

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.

The supply chain is an extremely important and complex system, which is widely related to the social system and the management system. The hierarchical scheduling and production planning of a dynamic supply chain can enable enterprises in the supply chain to obtain, and maintain, stable and lasting competitive advantages; thus, improving the overall competitiveness of the supply chain. Simultaneously, research on supply chains is also a hotspot in system engineering. At present, research on complex supply chain systems with dual channels is insufficient, and analysis of dynamic supply chains with supply failure of goods is rare. In the epidemic era, dynamic supply chain management was affected by the epidemic and became a very challenging topic. The control of the supply chain system under the impact of an epidemic situation is particularly important. This paper focused on H∞ the fault-tolerant control of a complex supply chain system with dual channels. First, from the perspective of engineering practice and green production, we established a new green supply chain model. This supply chain model includes the dual-channel supply of goods and also considers the supply failure of goods. At the same time, production delay and supply delay are also considered in this model. Second, a supply scheduling scheme was designed through cybernetics to ensure the stability of a supply chain with dual channels under supply failure of goods, and we completed supply chain management. Finally, the effectiveness of our results was verified by specific Chinese enterprise data.

Duality analysis of time series and complex networks has been a frontier topic during the last several decades. According to some recent approaches in this direction, the intrinsic dynamics of typical nonlinear systems can be better characterized by considering the related nonlinear time series from the perspective of networks science. In this paper, the associated network family of the unified piecewise-linear (PWL) chaotic family, which can bridge the gap of the PWL chaotic Lorenz system and the PWL chaotic Chen system, was firstly constructed and analyzed. We constructed the associated network family via the original and the modified frequency-degree mapping strategy, as well as the classical visibility graph and horizontal visibility graph strategy, after removing the transient states. Typical related network characteristics, including the network fractal dimension, of the associated network family, are computed with changes of single key parameter α. These characteristic vectors of the network are also compared with the largest Lyapunov exponent (LLE) vector of the related original dynamical system. It can be found that, some network characteristics are highly correlated with LLE vector of the original nonlinear system, i.e., there is an internal consistency between the largest Lyapunov exponents, some typical associated network characteristics, and the related network fractal dimension index. Numerical results show that the modified frequency-degree mapping strategy can demonstrate highest correlation, which means it can behave better to capture the intrinsic characteristics of the unified PWL chaotic family.

There is increasing evidence supporting the additional utility of nonlinear techniques such as chaos analysis of heart rate (HR) time series as indictors of prognosis in cardiac patients. Prolongation of rate-corrected QT interval, QTc, is strongly associated with sudden cardiac death. Recent studies of beat-to-beat QT interval variability (QTV) have shown that an increase in QTV is associated with increased sympathetic activity. QTvi, a QT variability index (QT variance corrected for mean QT divided by HR variance corrected for mean HR), is also a predictor of sudden cardiac death. We studied the utility of a measure of chaos, the Largest Lyapunov Exponent (LLE) of beat-to-beat HR and QT time series at baseline and after treatment in patients with congestive heart failure (CHF). We compared beat-to-beat HR and QT interval data in 23 patients with CHF and 19 age-matched normal controls. The ECG data were acquired in lead II configuration at a sampling rate of 1000 Hz. CHF patients had a significantly lower LLE of HR and a significantly higher LLE of QT time series than did normal controls. Clinical improvement in a subgroup of these patients was associated with a decrease in QT-LLE and a decrease in LLEqthr (LLE-QT/LLE-HR). These results demonstrate a decreased chaos of HR and increased chaos of QT time series in patients with CHF suggesting decreased cardiac vagal and increased sympathetic function in patients with CHF. Nonlinear measures may prove to be of additional utility to linear measures as surrogate end points to evaluate treatment effect in these patients.

Measures of LLE of heart rate in different frequency bands: a possible measure of relative vagal and sympathetic activity

A novel approach to determine the impact level of each step along the supply chain on strawberry quality

Designing and analyzing new chaotic systems with desired properties has gotten much interest recently. Through applying modification in a recent rare chaotic flow which has adjustable Kaplan–Yorke dimension, a flexible chaotic system is introduced in this work. In the mentioned modification, two parameters are added which can control amplitude of the attractor and largest Lyapunov exponent. Statistical and dynamical properties of such system could be discovered by applying stability analysis, estimating Lyapunov exponents, local Kaplan–Yorke dimension, and plots of state space. Interestingly, this system is in group of systems which have coexisting attractors, so it is a multistable chaotic system. By considering a practical application of this rare system, meaningful relation between the value of local Kaplan–Yorke dimension and the ability of the system as a random number generator can be seen in statistical tests.

This paper presents a new 4D chaotic system by extending a 3D system to investigate chaotic systems2 with hidden attractors further and explore their engineering applications in color image encryption. The system has hyperbolic shape equilibriums and the equilibriums are nonhyperbolic which is interesting and rarely mentioned before. The system has been investigated deeply by phase plot, time series, the largest Lyapunov exponent, bifurcation diagram, Poincaré map and 0–1 test. A coexisting hidden attractor has been found in this new system and the circuit simulation model of the system is built by Power Simulation (PSIM). Circuit simulation results are consistent with results of numerical simulations which verify its dynamic behavior further. Then, by combining the generalized Arnold transform with the new chaotic system, a new color image encryption algorithm has been proposed which has large key space and can encrypt either square images or nonsquare images with different size. Finally, the results of encryption experiment and security analysis prove the effectiveness of the algorithm.

The super market revolution has been underway in developing countries. Market research says that larger the numbers of economic agents involved in marketing and lesser their incomes’ share in consumer price’. The prospective solution to this problem may be consolidation of supply chain. The main motive of this paper is to explore the ways or super markets models that will integrate the small and marginal farmers with supply chain system in India. Information on marketing models and marketing institutions which deal fruits and vegetables in the country were analyzed. The fruits and vegetable commodities reach the final consumer through various channels. Among all the channels the direct market models are the best because the producer share in consumer rupee is 100 per cent and will eliminate middlemen completely. India opened up post – 1990, a number of new liberalized public markets operating direct marketing model with forward linkages for fruits and vegetables. The economic reforms also lead to the emergence a number of new private retail markets for fruits and vegetable with direct marketing models with backward linkages. The results reveal that private super markets will save farmers from transport, marketing cost and other charges and complete eliminate middlemen. Farmers who supply to private super markets have many advantages it includes technical guidance, market information on prices, perfect weights and spot payments etc. The opportunities include development of high value commodities market supply chain. The farmers are suggested for effective and efficient marketing of fruits and vegetables, the super markets have to purchase entire quantity brought by the farmer irrespective of grading, Export linkage is suggested, Government has to regulate prices, Government has to open and operate retail outlets, Government should assess the production and consumption level and announce the MSP accordingly. Even the farmers of the most of the states are adopting traditional marketing channels. The study suggests that modern direct marketing models to adopt.

The dynamics of network traffic are complex and nonlinear, and chaotic behaviors and their prediction, which play an important role in local area networks (LANs), are studied in detail, using the largest Lyapunov exponent. With the introduction of phase space reconstruction based on the time sequence, the high-dimensional traffic is projected onto the low dimension reconstructed phase space, and a reduced dynamic system is obtained from the dynamic system viewpoint. Then, a numerical method for computing the largest Lyapunov exponent of the low-dimensional dynamic system is presented. Further, the longest predictable time, which is related to chaotic behaviors in the system, is studied using the largest Lyapunov exponent, and the Wolf method is used to predict the evolution of the traffic in a local area network by both Dot and Interval predictions, and a reliable result is obtained by the presented method. As the conclusion, the results show that the largest Lyapunov exponent can be used to describe the sensitivity of the trajectory in the reconstructed phase space to the initial values. Moreover, Dot Prediction can effectively predict the flow burst. The numerical simulation also shows that the presented method is feasible and efficient for predicting the complex dynamic behaviors in LAN traffic, especially for congestion and attack in networks, which are the main two complex phenomena behaving as chaos in networks.