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Solving an Intractable Stochastic Partial Backordering Inventory Problem Using Machine Learning

  • Nidhi SrivastavEmail author
  • Achin Srivastav
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 985)

Abstract

This paper addresses the intractability of order crossover in a partial backordering inventory problem. Here, the Artificial Neural Network (ANN), which is a machine leaning algorithm is used to solve a stochastic inventory problem. The results for examining order crossover with the back-propagation ANN shows notable reduction in inventory cost in comparison to linear regression method. A numerical study is taken to demonstrate the findings. This paper further draws insight on effectiveness of machine learning in comparison to regression.

Keywords

ANN Order crossover Machine learning 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSKITJaipurIndia
  2. 2.Department of Mechanical EngineeringSKITJaipurIndia

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