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An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming

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Listed:
  • Hui Huang

    (College of Economics and Business Administration, Chongqing University, Chongqing 400044, China)

  • Yuyu Li

    (College of Computer and Information Science, Chongqing Normal University, Chongqing 400047, China)

  • Bo Huang

    (College of Economics and Business Administration, Chongqing University, Chongqing 400044, China)

  • Xing Pi

    (College of Social Science, Third Military Medical University, Chongqing 400038, China)

Abstract

In order to recycle and dispose of all people’s expired drugs, the government should design a subsidy policy to stimulate users to return their expired drugs, and drug-stores should take the responsibility of recycling expired drugs, in other words, to be recycling stations. For this purpose it is necessary for the government to select the right recycling stations and treatment stations to optimize the expired drug recycling logistics network and minimize the total costs of recycling and disposal. This paper establishes a tri-level programming model to study how the government can optimize an expired drug recycling logistics network and the appropriate subsidy policies. Furthermore, a Hybrid Genetic Simulated Annealing Algorithm (HGSAA) is proposed to search for the optimal solution of the model. An experiment is discussed to illustrate the good quality of the recycling logistics network and government subsides obtained by the HGSAA. The HGSAA is proven to have the ability to converge on the global optimal solution, and to act as an effective algorithm for solving the optimization problem of expired drug recycling logistics network and government subsidies.

Suggested Citation

  • Hui Huang & Yuyu Li & Bo Huang & Xing Pi, 2015. "An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming," IJERPH, MDPI, vol. 12(7), pages 1-14, July.
    • Handle: RePEc:gam:jijerp:v:12:y:2015:i:7:p:7738-7751:d:52312
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    References listed on IDEAS

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    1. Hui Huang & Yan Jin & Bo Huang & Han-Guang Qiu, 2014. "Mixed Replenishment Policy for ATO Supply Chain Based on Hybrid Genetic Simulated Annealing Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-9, March.
    2. Sameer Kumar & Erin Dieveney & Aaron Dieveney, 2009. "Reverse logistic process control measures for the pharmaceutical industry supply chain," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 58(2), pages 188-204, January.
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    Cited by:

    1. Jun Lv & Xuan Liu & Sivhuang Lay, 2021. "The Impact of Consequences Awareness of Public Environment on Medicine Return Behavior: A Moderated Chain Mediation Model," IJERPH, MDPI, vol. 18(18), pages 1-19, September.
    2. Faez Alnahas & Prince Yeboah & Louise Fliedel & Ahmad Yaman Abdin & Khair Alhareth, 2020. "Expired Medication: Societal, Regulatory and Ethical Aspects of a Wasted Opportunity," IJERPH, MDPI, vol. 17(3), pages 1-17, January.

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