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Study on Predicting Returns of White Goods Based on Markov

Excerpt

Close Loop Supply Chains (CLSC) is one of development trends of supply chain. Reverse flow forecast of waste products plays an important role in supply chain network planning, purchasing, production planning and inventory controlling, which is one of the key technologies in the supply chain management cycle. This paper, taking re-manufacturing CLSC as target, researches reverse flow forecast technology and method based on low of Markov.

Main factors and complexity of forecast are analyzed from respects of product life cycle, features of product consumption point, recycling channels, sales trends and changes in consumer buying behavior characteristics. Based on Markov forecast, taking characteristics of white goods into consideration, mathematical model of forecast the quantity of white goods flow in reverse logistics in CLSC is studied and established. Finally, MATLAB tools are used to forecast practical case, and then, Law of Markov is evaluated according to the results.

  • Abstract
  • Key words
  • Introduction
  • Factors Influencing Reverse Flow Prediction
  • Prediction Model for Reverse Flow Based on the Markov
  • The Example of Reverse Flow Prediction in White Goods
  • Conclusions
  • References

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