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Economic and environmental comparison of grouping strategies in coordinated multi-item inventory systems

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  • Dinçer Konur

    (Missouri University of Science and Technology, Rolla, USA)

  • Brian Schaefer

    (Missouri University of Science and Technology, Rolla, USA)

Abstract

The increasing concerns for sustainability throughout supply chains are enforcing managers to plan their operations considering not only economic but also environmental performance. Inventory management is one of the main determinants of the costs incurred and emissions generated throughout supply chains as it defines the level of logistical operations, freight transportation, and warehousing activities. In this study, we analyze a multi-item inventory control system with coordinated shipments. In particular, we revisit the well-known deterministic joint replenishment problem (JRP) with economic and environmental objectives under indirect and direct grouping strategies. We formulate and develop solution methods for each bi-objective JRP and compare direct and indirect grouping strategies with respect to their economic as well as environmental performance. A set of numerical studies is presented to examine the settings where a specific grouping strategy can be economically and environmentally better than the other.

Suggested Citation

  • Dinçer Konur & Brian Schaefer, 2016. "Economic and environmental comparison of grouping strategies in coordinated multi-item inventory systems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(3), pages 421-436, March.
    • Handle: RePEc:pal:jorsoc:v:67:y:2016:i:3:p:421-436
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    Citations

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    Cited by:

    1. Aleksander Banasik & Jacqueline M. Bloemhof-Ruwaard & Argyris Kanellopoulos & G. D. H. Claassen & Jack G. A. J. Vorst, 2018. "Multi-criteria decision making approaches for green supply chains: a review," Flexible Services and Manufacturing Journal, Springer, vol. 30(3), pages 366-396, September.
    2. Young Hyeon Yang & Jong Soo Kim, 2020. "An adaptive joint replenishment policy for items with non-stationary demands," Operational Research, Springer, vol. 20(3), pages 1665-1684, September.
    3. Konur, Dinçer, 2017. "Non-collaborative emission targets joining and quantity flow decisions in a Stackelberg setting," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 60-82.
    4. Daiki Min & Kwanghun Chung, 2017. "A Joint Optimal Decision on Shipment Size and Carbon Reduction under Direct Shipment and Peddling Distribution Strategies," Sustainability, MDPI, vol. 9(11), pages 1-21, November.
    5. Xiaoqing Zhao & Sinan Li & Junwei Pu & Peipei Miao & Qian Wang & Kun Tan, 2019. "Optimization of the National Land Space Based on the Coordination of Urban-Agricultural-Ecological Functions in the Karst Areas of Southwest China," Sustainability, MDPI, vol. 11(23), pages 1-20, November.
    6. Konur, Dinçer & Campbell, James F. & Monfared, Sepideh A., 2017. "Economic and environmental considerations in a stochastic inventory control model with order splitting under different delivery schedules among suppliers," Omega, Elsevier, vol. 71(C), pages 46-65.
    7. Jen-Yen Lin & Ming-Jong Yao, 2020. "The joint replenishment problem with trade credits," Journal of Global Optimization, Springer, vol. 76(2), pages 347-382, February.
    8. Yann Bouchery & Asma Ghaffari & Zied Jemai & Jan Fransoo, 2016. "Sustainable transportation and order quantity: insights from multiobjective optimization," Flexible Services and Manufacturing Journal, Springer, vol. 28(3), pages 367-396, September.

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