Abstract
Supply chain management is important for coal companies and organizations to improve their business and enhance competitiveness in the Chinese marketplace. The bullwhip effect problem of coal supply chain systems with all demands, lead times, and ordering quantities in an uncertain environment is addressed in this paper. To simulate the bullwhip effect, the Hong Fuzzy Time Series approach and Genetic Algorithm module are preferred as a superior forecasting model. And then a back propagation Neural Network module is added to defuzzify the output of the proposed model. So the bullwhip effect is calculated and analyzed here. The effectiveness and flexibility of proposed method is verified through simulation study.
Highlights
China is the largest energy consumer in the world
To assess the performance of proposed uncertainty-dependent coal supply chain method and to gain further insights into the dynamical characteristics of supply chain systems with order placement lead time delays in an uncertain environment, especially the bullwhip phenomenon, we carry out simulations
We have studied the bullwhip effect problem in uncertain coal supply chain systems
Summary
China is the largest energy consumer in the world. Providing sufficient coal supply to meet the requirements of a huge population with rising living standards will be a difficult task. With increasingly competitive coal market and high coal consumption, the coal supply chain has become critical and strategic to long-term development in China. Multiple independent mines are often connected to a shared rail network. A common phenomenon in the coal supply chain management that has been observed and justified is known as ‘‘bullwhip effect”[1]. Padmanabhan, and Whang have identified five major causes for bullwhip effect in the supply chain. They are listed as demand forecasting, order batching, price fluctuations, supply shortages and non-zero lead-time[2]. According to Sterman, the bullwhip effect originates from the non-optimal solutions adopted by a supply chain participant while does not consider the supply system as a whole[3]
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