scholarly journals Model retraining and information sharing in a supply chain with long-term fluctuating demands

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Takahiro Ezaki ◽  
Naoto Imura ◽  
Katsuhiro Nishinari

AbstractDemand forecasting based on empirical data is a viable approach for optimizing a supply chain. However, in this approach, a model constructed from past data occasionally becomes outdated due to long-term changes in the environment, in which case the model should be updated (i.e., retrained) using the latest data. In this study, we examine the effects of updating models in a supply chain using a minimal setting. We demonstrate that when each party in the supply chain has its own forecasting model, uncoordinated model retraining causes the bullwhip effect even if a very simple replenishment policy is applied. Our results also indicate that sharing the forecasting model among the parties involved significantly reduces the bullwhip effect.

2021 ◽  
Vol 11 (18) ◽  
pp. 8612
Author(s):  
Santanu Kumar Dash ◽  
Michele Roccotelli ◽  
Rasmi Ranjan Khansama ◽  
Maria Pia Fanti ◽  
Agostino Marcello Mangini

The long-term electricity demand forecast of the consumer utilization is essential for the energy provider to analyze the future demand and for the accurate management of demand response. Forecasting the consumer electricity demand with efficient and accurate strategies will help the energy provider to optimally plan generation points, such as solar and wind, and produce energy accordingly to reduce the rate of depletion. Various demand forecasting models have been developed and implemented in the literature. However, an efficient and accurate forecasting model is required to study the daily consumption of the consumers from their historical data and forecast the necessary energy demand from the consumer’s side. The proposed recurrent neural network gradient boosting regression tree (RNN-GBRT) forecasting technique allows one to reduce the demand for electricity by studying the daily usage pattern of consumers, which would significantly help to cope with the accurate evaluation. The efficiency of the proposed forecasting model is compared with various conventional models. In addition, by the utilization of power consumption data, power theft detection in the distribution line is monitored to avoid financial losses by the utility provider. This paper also deals with the consumer’s energy analysis, useful in tracking the data consistency to detect any kind of abnormal and sudden change in the meter reading, thereby distinguishing the tampering of meters and power theft. Indeed, power theft is an important issue to be addressed particularly in developing and economically lagging countries, such as India. The results obtained by the proposed methodology have been analyzed and discussed to validate their efficacy.


2021 ◽  
Author(s):  
Arora Ankit ◽  
Rajagopal Rajesh

Abstract The automobile sector in India is one the key segment of Indian economy as it contributes to 4% of India’s GDP and 5% of India’s Industrial production. The supply chain of any firm is generally dependent on six driving factors out of which three are functional (information, inventory, and facilities) and 3 are logistic (sourcing, pricing, and transportation). The risk causing factors in supply chains consists of various levels of sub-factors under them. Say for instance, under supply risk, the sub-factors can be poor logistics at supplier end, poor material quality etc., under demand risk, the sub-factors can be inaccurate demand forecasting, fluctuating demand, bullwhip effect, and under logistics risk, the sub-factors can be poor transportation network, shorter lead time, stock outs. Through this study, we observe to find the effect of these factors in the supply chain. We use Failure Mode and Effect Analysis (FMEA) technique to prioritize the various types of risk into zones namely high, medium and low risk factors. Also, we use the Best Worst Method (BWM), a multi-criteria decision-making technique to find out the overall weightings of different risk factors. The combination of these methods can help an organization to prioritize various risk factors and proposing a proper risk mitigation strategy leading to increase in overall supply chain efficiency and responsiveness.


1970 ◽  
Vol 25 (2) ◽  
pp. 177-188 ◽  
Author(s):  
Francisco Campuzano-Bolarín ◽  
Antonio Guillamón Frutos ◽  
Ma Del Carmen Ruiz Abellón ◽  
Andrej Lisec

The research of the Bullwhip effect has given rise to many papers, aimed at both analysing its causes and correcting it by means of various management strategies because it has been considered as one of the critical problems in a supply chain. This study is dealing with one of its principal causes, demand forecasting. Using different simulated demand patterns, alternative forecasting methods are proposed, that can reduce the Bullwhip effect in a supply chain in comparison to the traditional forecasting techniques (moving average, simple exponential smoothing, and ARMA processes). Our main findings show that kernel regression is a good alternative in order to improve important features in the supply chain, such as the Bullwhip, NSAmp, and FillRate.


Author(s):  
Camilla Gåfvels

This article investigates how expressions of vocational knowing regarding colour and form changed in Swedish upper secondary floristry education between 1990 and 2015. An analytical approach is used which falls within the framework of a sociocultural interpretation of educational activity. During the period studied, subject matter related to colour and form became increasingly formalised. Empirical data was obtained from multiple sources, including two interviews with an experienced senior teacher, which helped to reveal the local history of a leading Swedish floristry school. The findings of the article are as follows: (i) conceptualisation, verbal analysis and reflection have gained prominence in Swedish floristry education since the 1990s, and (ii) these tools have increasingly served to help participants in education make and express aesthetic judgements. Through a discussion of various aspects of contemporary Swedish floristry education, the article illuminates the complexity of long-term changes in vocational knowing.


Open Physics ◽  
2017 ◽  
Vol 15 (1) ◽  
pp. 247-252 ◽  
Author(s):  
Yue Li ◽  
Qi-Jie Jiang

AbstractInformation asymmetry and the bullwhip effect have been serious problems in the tourism supply chain. Based on platform theory, this paper established a mathematical model to explore the inner mechanism of a platform’s influence on stakeholders’ ability to forecast demand in tourism. Results showed that the variance of stakeholders’ demand predictions with a platform was smaller than the variance without a platform, which meant that a platform would improve predictions of demand for stakeholders. The higher information-processing ability of the platform also had other effects on demand forecasting. Research on the inner logic of the platform’s influence on stakeholders has important theoretical and realistic value. This area is worthy of further study.


2012 ◽  
Vol 23 (2) ◽  
pp. 131-140 ◽  
Author(s):  
Francisco Campuzano Bolarín ◽  
Antonio Guillamón Frutos ◽  
Andrej Lisec

Price fluctuation is a practice commonly used by companies to stimulate demand and a main cause of the Bullwhip effect. Assuming a staggered step demand pattern that responds elastically to retailer’s price fluctuation, and by using a supply chain management dynamic model, we will analyse the impact of these fluctuations on the variability of the orders placed along a traditional multilevel supply chain. Subsequently, the results obtained will serve to propose a forecasting model enabling to calculate the potential variability of orders placed by each echelon on the basis of the price pattern used. Finally, under the hypothesis of an environment of collaboration between the different members of the chain, we propose a predictive model that makes it possible to quantify the distortion of the orders generated by each level. KEYWORDS: Bullwhip effect, systems dynamics, price fluctuation, supply chain management


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