A location-inventory-routing problem to design a circular closed-loop supply chain network with carbon tax policy for achieving circular economy: An augmented epsilon-constraint approach

Kannan Govindan*, Farhad Salehian, Hadi Kian, Seyed Teimoor Hosseini, Hassan Mina

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

The emergence of the circular economy concept has pushed industry owners towards the green supply chain and waste reduction. The closed-loop supply chain originates from the concept of the circular economy and its purpose is to increase efficiency and profitability by reducing waste and energy consumption. Hence, in this research, an integrated bi-objective mixed-integer linear programming model is developed with the aim of optimizing both operational and strategic decisions in a closed-loop supply chain network. The proposed model benefits the location-inventory-routing problem to structure the network, and it applies a carbon tax policy and vehicle scheduling problem to reduce emissions and vehicle waiting time, respectively. Considering problems such as split-delivery, storage possibility, shortage, supplier selection, order allocation, heterogenous vehicles, and uncertain demand has led to the development of a comprehensive model. A stochastic scenario-based approach is used to deal with demand uncertainty, and an augmented epsilon-constraint method is employed to solve the proposed bi-objective model. The applicability of the proposed model and the effectiveness of the bi-objective solution approach for achieving circular economy are examined through its implementation in a cable and wire industry in Iran.

Original languageEnglish
Article number108771
JournalInternational Journal of Production Economics
Volume257
Number of pages18
ISSN0925-5273
DOIs
Publication statusPublished - Mar 2023

Keywords

  • Carbon tax policy
  • Circular closed-loop supply chain
  • Epsilon-constraint method
  • Location-inventory-routing problem
  • Vehicle scheduling problem

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