Journal of Production Engineering

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Vol. 23 No. 1 (2020)
Original Research Article

Multi-channel supply chain optimisation in cyber-physical environment under quantity discounts

Ágota Bányai
University of Miskolc, Faculty of Mechanical Engineering and Informatics, Institute of Logistics, 3515 Miskolc, Hungary
Dmitry Efimenko
Logistics and Transportation Problems, Moscow Automobile and Road Construction State Technical University
Illés Béla
University of Miskolc, Faculty of Mechanical Engineering and Informatics, Institute of Logistics, 3515 Miskolc, Hungary
Peter Tamás
University of Miskolc, Faculty of Mechanical Engineering and Informatics, Institute of Logistics, 3515 Miskolc, Hungary
Tamás Bányai
University of Miskolc, Faculty of Mechanical Engineering and Informatics, Institute of Logistics, 3515 Miskolc, Hungary

Published 2020-06-30

abstract views: 28 // FULL TEXT ARTICLE (PDF): 20


Keywords

  • logistics,
  • multi-channel supply chain,
  • nonlinear regression,
  • purchasing

How to Cite

Bányai, Ágota, Efimenko, D., Béla, I., Tamás, P., & Bányai, T. (2020). Multi-channel supply chain optimisation in cyber-physical environment under quantity discounts. Journal of Production Engineering, 23(1), 65–70. https://doi.org/10.24867/JPE-2020-01-065

Abstract

The procurement, manufacturing, distribution, and recycling processes within the circular economy have undergone significant changes. The increasing complexity of these processes has necessitated the application of new models, methods, tools, and technologies. Multi- and omni-channel purchasing and distribution solutions have introduced new challenges for researchers, prompting the exploration of novel models and algorithms to support the optimal design and operation of these processes. In this article, the authors present a mathematical model of a multi-channel supply chain solution within a cyber-physical environment, where the purchasing processes involving suppliers and customers are integrated within a supply chain cloud. Numerical analysis is conducted to validate the described model.

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