IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v184y2024ics1366554524000826.html
   My bibliography  Save this article

A multi-objective optimization model for medical waste recycling network design under uncertainties

Author

Listed:
  • Shen, Liang
  • Xu, Xiang
  • Shao, Feng
  • Shao, Hu
  • Ge, Yanxin

Abstract

Transporting medical waste (MW) generated by medical institutions (MIs) is a process that poses potential threats to the environment and public safety. Therefore, it is vital to find a safe and efficient way to transport this type of waste to disposal centers (DCs). However, there are challenges in the transportation of MW due to random factors such as the generation of waste in an unpredictable manner and unforeseen travel times. In this paper, we propose a bi-level optimization model to minimize site selection costs, transportation costs, time-window penalties costs, and transportation risks under uncertainties. The concepts of “loading reliability”, “travel time reliability” and “transportation risk” are adopted in the proposed optimization model. The simulated annealing algorithm (SA) is employed to address the optimal location problem (Upper level), which involves minimizing the construction cost, transportation cost (DC-CP-DC), and transportation risk (estimated using Bayesian method). To tackle the capacity-constrained vehicle routing problem considering transportation risk and time window penalties (Lower level), we propose an improved genetic algorithm named harmony search algorithm (IHSGA). Subsequently, the results from the lower level are looped back to the upper level, fostering mutual influence between the two stages. We demonstrate the effectiveness and correctness of the proposed model and algorithm using S city in China as an illustrative example. Furthermore, a series of sensitivity analyses were conducted to examine the impact of various factors. The findings highlight the pivotal roles of both travel time reliability and loading reliability in designing the medical waste recycling network. In comparison to the general Genetic Algorithm (GA) and CPLEX solver, the modified IHSGA presented in this paper exhibits superior performance.

Suggested Citation

  • Shen, Liang & Xu, Xiang & Shao, Feng & Shao, Hu & Ge, Yanxin, 2024. "A multi-objective optimization model for medical waste recycling network design under uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    • Handle: RePEc:eee:transe:v:184:y:2024:i:c:s1366554524000826
    DOI: 10.1016/j.tre.2024.103492
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554524000826
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2024.103492?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lam, William H.K. & Shao, Hu & Sumalee, Agachai, 2008. "Modeling impacts of adverse weather conditions on a road network with uncertainties in demand and supply," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 890-910, December.
    2. Srinivasan, Karthik K. & Prakash, A.A. & Seshadri, Ravi, 2014. "Finding most reliable paths on networks with correlated and shifted log–normal travel times," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 110-128.
    3. Wanting Zhang & Ming Zeng & Peng Guo & Kun Wen, 2022. "Variable Neighborhood Search for Multi-Cycle Medical Waste Recycling Vehicle Routing Problem with Time Windows," IJERPH, MDPI, vol. 19(19), pages 1-25, October.
    4. Mo, Pengli & Yao, Yu & D’Ariano, Andrea & Liu, Zhiyuan, 2023. "The vehicle routing problem with underground logistics: Formulation and algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    5. Erhan Erkut & Armann Ingolfsson, 2000. "Catastrophe Avoidance Models for Hazardous Materials Route Planning," Transportation Science, INFORMS, vol. 34(2), pages 165-179, May.
    6. Huo Chai & Ruichun He & Ronggui Kang & Xiaoyan Jia & Cunjie Dai, 2023. "Solving Bi-Objective Vehicle Routing Problems with Driving Risk Consideration for Hazardous Materials Transportation," Sustainability, MDPI, vol. 15(9), pages 1-17, May.
    7. Zhang, Meng & Wang, Nengmin & He, Zhengwen & Jiang, Bin, 2021. "Vehicle routing optimization for hazmat shipments considering catastrophe avoidance and failed edges," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    8. Duan Li & Xiaoling Sun, 2006. "Nonlinear Integer Programming," International Series in Operations Research and Management Science, Springer, number 978-0-387-32995-6, April.
    9. Shen, Liang & Shao, Hu & Wu, Ting & Fainman, Emily Zhu & Lam, William H.K., 2020. "Finding the reliable shortest path with correlated link travel times in signalized traffic networks under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    10. Dongyan Chen & Chan He & Senlin Wu, 2016. "Single facility collection depots location problem with random weights," Operational Research, Springer, vol. 16(2), pages 287-299, July.
    11. Anastasios D. Vareias & Panagiotis P. Repoussis & Panagiotis P. Repoussi, 2019. "Assessing Customer Service Reliability in Route Planning with Self-Imposed Time Windows and Stochastic Travel Times," Service Science, INFORMS, vol. 53(1), pages 256-281, February.
    12. Zhenzhen Zhang & Zhixing Luo & Hu Qin & Andrew Lim, 2019. "Exact Algorithms for the Vehicle Routing Problem with Time Windows and Combinatorial Auction," Transportation Science, INFORMS, vol. 53(2), pages 427-441, March.
    13. H. Frank, 1969. "Shortest Paths in Probabilistic Graphs," Operations Research, INFORMS, vol. 17(4), pages 583-599, August.
    14. Nikzamir, Mohammad & Baradaran, Vahid, 2020. "A healthcare logistic network considering stochastic emission of contamination: Bi-objective model and solution algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    15. H. Asefi & S. Lim & M. Maghrebi & S. Shahparvari, 2019. "Mathematical modelling and heuristic approaches to the location-routing problem of a cost-effective integrated solid waste management," Annals of Operations Research, Springer, vol. 273(1), pages 75-110, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Bi Yu & Li, Qingquan & Lam, William H.K., 2016. "Finding the k reliable shortest paths under travel time uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 189-203.
    2. Shen, Liang & Shao, Hu & Wu, Ting & Fainman, Emily Zhu & Lam, William H.K., 2020. "Finding the reliable shortest path with correlated link travel times in signalized traffic networks under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    3. Tan, Zhijia & Yang, Hai & Guo, Renyong, 2014. "Pareto efficiency of reliability-based traffic equilibria and risk-taking behavior of travelers," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 16-31.
    4. Zang, Zhaoqi & Xu, Xiangdong & Yang, Chao & Chen, Anthony, 2018. "A closed-form estimation of the travel time percentile function for characterizing travel time reliability," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 228-247.
    5. Liang Shen & Feiran Wang & Yueyuan Chen & Xinyi Lv & Zongliang Wen, 2022. "A Reliability-Based Stochastic Traffic Assignment Model for Signalized Traffic Network with Consideration of Link Travel Time Correlations," Sustainability, MDPI, vol. 14(21), pages 1-18, November.
    6. Xu, Xiangdong & Chen, Anthony & Cheng, Lin & Yang, Chao, 2017. "A link-based mean-excess traffic equilibrium model under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 53-75.
    7. Zhaoqi Zang & Xiangdong Xu & Kai Qu & Ruiya Chen & Anthony Chen, 2022. "Travel time reliability in transportation networks: A review of methodological developments," Papers 2206.12696, arXiv.org, revised Jul 2022.
    8. A. Arun Prakash & Karthik K. Srinivasan, 2018. "Pruning Algorithms to Determine Reliable Paths on Networks with Random and Correlated Link Travel Times," Transportation Science, INFORMS, vol. 52(1), pages 80-101, January.
    9. Arun Prakash, A., 2020. "Algorithms for most reliable routes on stochastic and time-dependent networks," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 202-220.
    10. Wu, Xing, 2015. "Study on mean-standard deviation shortest path problem in stochastic and time-dependent networks: A stochastic dominance based approach," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 275-290.
    11. Hoang, Nam H. & Vu, Hai L. & Lo, Hong K., 2018. "An informed user equilibrium dynamic traffic assignment problem in a multiple origin-destination stochastic network," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 207-230.
    12. Xu, Xiangdong & Qu, Kai & Chen, Anthony & Yang, Chao, 2021. "A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    13. Mohri, Seyed Sina & Mohammadi, Mehrdad & Gendreau, Michel & Pirayesh, Amir & Ghasemaghaei, Ali & Salehi, Vahid, 2022. "Hazardous material transportation problems: A comprehensive overview of models and solution approaches," European Journal of Operational Research, Elsevier, vol. 302(1), pages 1-38.
    14. P. Daniel Wright & Matthew J. Liberatore & Robert L. Nydick, 2006. "A Survey of Operations Research Models and Applications in Homeland Security," Interfaces, INFORMS, vol. 36(6), pages 514-529, December.
    15. Timothy M. Sweda & Irina S. Dolinskaya & Diego Klabjan, 2017. "Adaptive Routing and Recharging Policies for Electric Vehicles," Transportation Science, INFORMS, vol. 51(4), pages 1326-1348, November.
    16. Cascón, J.M. & González-Arteaga, T. & de Andrés Calle, R., 2019. "Reaching social consensus family budgets: The Spanish case," Omega, Elsevier, vol. 86(C), pages 28-41.
    17. Murthy, Ishwar & Sarkar, Sumit, 1997. "Exact algorithms for the stochastic shortest path problem with a decreasing deadline utility function," European Journal of Operational Research, Elsevier, vol. 103(1), pages 209-229, November.
    18. Shao, Hu & Lam, William H.K. & Sumalee, Agachai & Chen, Anthony & Hazelton, Martin L., 2014. "Estimation of mean and covariance of peak hour origin–destination demands from day-to-day traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 52-75.
    19. Bi Chen & William Lam & Agachai Sumalee & Qingquan Li & Hu Shao & Zhixiang Fang, 2013. "Finding Reliable Shortest Paths in Road Networks Under Uncertainty," Networks and Spatial Economics, Springer, vol. 13(2), pages 123-148, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:184:y:2024:i:c:s1366554524000826. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.