Multiagent Methodology to Reduce the Bullwhip Effect in a Supply Chain

2014 ◽  
pp. 1-21
Author(s):  
Borja Ponte ◽  
Raúl Pino ◽  
David de la Fuente
Keyword(s):  
Supply Chain ◽  
Bullwhip Effect

A Review on the Application of Neural Networks for Decreasing Bullwhip Effect in Supply Chain

2015 ◽  
Vol 9 (5) ◽  
pp. 438
Author(s):  
Milad Yousefi ◽  
Moslem Yousefi ◽  
Ricardo Poley Martins Ferreira
Keyword(s):  
Neural Networks ◽  
Supply Chain ◽  
Bullwhip Effect

Classification of Operational and Financial Variables Affecting the Bullwhip Effect in Indian Sectors: A Machine Learning Approach

2019 ◽  
Vol 12 (3) ◽  
pp. 171-179 ◽  
Author(s):  
Sachin Gupta ◽  
Anurag Saxena
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Product Life Cycle ◽  
Consumer Preference ◽  
Bullwhip Effect ◽  
Machine Learning Techniques ◽  
Chain Management ◽  
Financial Variables

Background: The increased variability in production or procurement with respect to less increase of variability in demand or sales is considered as bullwhip effect. Bullwhip effect is considered as an encumbrance in optimization of supply chain as it causes inadequacy in the supply chain. Various operations and supply chain management consultants, managers and researchers are doing a rigorous study to find the causes behind the dynamic nature of the supply chain management and have listed shorter product life cycle, change in technology, change in consumer preference and era of globalization, to name a few. Most of the literature that explored bullwhip effect is found to be based on simulations and mathematical models. Exploring bullwhip effect using machine learning is the novel approach of the present study. Methods: Present study explores the operational and financial variables affecting the bullwhip effect on the basis of secondary data. Data mining and machine learning techniques are used to explore the variables affecting bullwhip effect in Indian sectors. Rapid Miner tool has been used for data mining and 10-fold cross validation has been performed. Weka Alternating Decision Tree (w-ADT) has been built for decision makers to mitigate bullwhip effect after the classification. Results: Out of the 19 selected variables affecting bullwhip effect 7 variables have been selected which have highest accuracy level with minimum deviation. Conclusion: Classification technique using machine learning provides an effective tool and techniques to explore bullwhip effect in supply chain management.

A Fuzzy agent-based model for reduction of bullwhip effect in supply chain systems

2008 ◽  
Vol 34 (3) ◽  
pp. 1680-1691 ◽  
Author(s):  
M.H. Fazel Zarandi ◽  
M. Pourakbar ◽  
I.B. Turksen
Keyword(s):  
Supply Chain ◽  
Bullwhip Effect ◽  
Agent Based Model ◽  
Agent Based

Buffet Effect Simulation Model on Demand Chain Management

2010 ◽  
Vol 44-47 ◽  
pp. 688-692
Author(s):  
Xiao Yan Wang ◽  
Jian Sun
Keyword(s):  
Supply Chain ◽  
Side Information ◽  
Bullwhip Effect ◽  
Chain Management ◽  
Demand Chain ◽  
Supply Chain Efficiency ◽  
Demand Fluctuations ◽  
Partner Collaboration ◽  
Transmission Ability ◽  
Demand Chain Management

Bullwhip effect means the magnification of demand fluctuations, which is evident in a supply chain when demand increases and decreases, while the concept of Demand Chain Management means to make the planning on the basis of the demand side information so as to solve the problem of inconsistent upstream and downstream information by means of partner collaboration in the supply chain. Demand chain emphasizes the customer demand as its core value so as to achieve the best balance between the supply chain efficiency and customer satisfaction. Compared with the supply chain, the demand chain advises the enterprise to strengthen the information transmission ability to promote the performance. Under the demand chain management, the extent of bullwhip effect are weakened, and the fluctuation range against demand chain management is lower than against traditional supply chain.

Vertical Contracts in a Supply Chain and the Bullwhip Effect

2020 ◽  
Author(s):  
Zhan Qu ◽  
Horst Raff
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Operations Management ◽  
Bullwhip Effect ◽  
Price Effect ◽  
Demand Shocks

This paper shows that decentralized supply chains, in which upstream firms use linear wholesale prices, may experience lower upstream production and downstream sales volatility than vertically integrated supply chains and may be less susceptible to the bullwhip effect by which the variance of upstream production exceeds the variance of downstream sales. The reason is that decentralized supply chains exhibit a price effect, whereby upstream producers raise wholesale prices in the case of positive demand shocks and lower wholesale prices in the case of negative demand shocks. Whereas upstream producers benefit from the price effect and, thus, from a dampening of the bullwhip effect, downstream firms may lose, and overall supply chain profit may decrease. This paper was accepted by Vishal Gaur, operations management.

Optimization Control of the Bullwhip Effect in Supply Chain Inventory

2014 ◽  
Vol 945-949 ◽  
pp. 3187-3190
Author(s):  
Hai Dong ◽  
Jin Hua Liu ◽  
Liang Yu Liu
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Control Theory ◽  
Inventory Control ◽  
Pid Controller ◽  
Bullwhip Effect ◽  
Control Gain ◽  
Optimization Control ◽  
Suitable Combination ◽  
The Mathematical Model

The bullwhip effect was caused by fuzzy demand among the enterprises. In order to reduce this effect, control theory was applied to solve the inventory in supply chain. Firstly, inventory control in supply chain and the bullwhip effect was researched. Secondly, a kind of proportional integral differential (PID) controller was developed for inventory control in a three-level supply chain, and the mathematical model of the PID controller for inventory control was presented. Finally, the results show that the PID controller can evidently alleviate the bullwhip effect and inventory fluctuations under the suitable combination of control gain.

scholarly journals Engineering patterns of supply chain optimization to manage oscillation effect

2017 ◽  
Vol 15 (2) ◽  
pp. 124-139
Author(s):  
Thokozani Patmond Mbhele
Keyword(s):  
Supply Chain ◽  
Sampling Technique ◽  
Bullwhip Effect ◽  
Modern Technology ◽  
Supply Chain Optimization ◽  
Upstream Site ◽  
Oscillation Effect ◽  
Innovative Strategies ◽  
Product Availability ◽  
Real Time Information

The cascading order variability from downstream trumping up the upstream site of the supply chain network indicates the deleterious effect to the performance of the fast moving consumer goods industry. The fundamental likelihood to optimization in this industry requires dexterous flows of quasi-real-time information, as well as reliable product availability. In this context, this study analyzes the challenges of bullwhip effect on the perspective of ingenious optimization strategies, and further contemplates to establish the engineering patterns of interrelationships on the magnitude of pooling the resources to advance supply chain capabilities. The suppression of bullwhip effect on underlying optimization strategies is sought to elevate accelerated responsiveness, improve network demand visibility and reduce volatility in frequencies to inventory replenishment. A rigorous and disciplined quantitative approach afforded the tentatively development of pattern of interrelated supply chain dimensions. The factor analysis method was used on 448 responses and insightful findings were produced from the compelling purposive sampling technique. The findings indicate that the magnitude of better ameliorating bullwhip effect, the value of competitive economic information and strength of selected optimization strategies depend on the model of unified engineering patterns. This paper provides insights to FMCG industry on using innovative strategies and modern technology to enhance supply chain visibility through integrated systems networks.

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