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A healthcare logistic network considering stochastic emission of contamination: Bi-objective model and solution algorithm

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  • Nikzamir, Mohammad
  • Baradaran, Vahid

Abstract

This paper presents a novel healthcare waste location-routing problem by concentrating on a new perspective in healthcare logistics networks. In this problem, there are healthcare, treatment, and disposal centers. Locations of healthcare centers are known, however, it is required to select appropriate locations for treatment, recycling, and disposal centers. Healthcare wastes are divided into infectious and non-infectious wastes. Since a great volume of healthcare wastes are infectious, the emission of contamination can have obnoxious impacts on the environment. The proposed problem considers a stochastic essence for the emission of contamination which depends on the transferring times. In this respect, transferring times between healthcare and treatment centers have been considered as normal random variables. As transferring time increases, it is more likely for the contamination to spread. Having visited a treatment center, infectious wastes are sterilized and they will no longer be harmful to the environment. This research develops a bi-objective mixed-integer mathematical formulation to tackle this problem. The objectives of this model are minimization of total costs and emission of contamination, simultaneously. Complexity of the proposed problem led the researchers to another contribution. This study also develops a Multi-Objective Water-Flow like Algorithm (MOWFA), which is a meta-heuristic, to solve the problem. This algorithm uses a procedure based on the Analytical Hierarchy Process (AHP) to rank the non-dominated solutions in the archive set. By means of a developed mating operator, the MOWFA utilizes the best ranked solutions of the archive in order to obtain high quality offspring. Two neighborhood operators have been designed for the MOWFA as the local search methods. Extensive computational experiments have been conducted to evaluate the effectiveness of the MOWFA on several test problems compared with other meta-heuristics, namely the Multi-Objective Imperialist Competitive Algorithm (MOICA) and Multi-Objective Simulated Annealing (MOSA). These experiments also include a real healthcare waste logistic network in Iran. The computational experiments demonstrate that our proposed algorithm prevails these algorithms in terms of some well-known performance evaluation measures.

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  • 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).
    • Handle: RePEc:eee:transe:v:142:y:2020:i:c:s1366554520307110
    DOI: 10.1016/j.tre.2020.102060
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    References listed on IDEAS

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    Cited by:

    1. Shang, Xiaoting & Zhang, Guoqing & Jia, Bin & Almanaseer, Mohammed, 2022. "The healthcare supply location-inventory-routing problem: A robust approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    2. Guo Chen & Jiapeng Chen, 2023. "Reverse Logistics Network Model of Dual-Channel Recycling Boxes Based on Genetic Algorithm Optimization: A Multi-Objective and Uncertain Environment Perspective," Sustainability, MDPI, vol. 15(5), pages 1-24, March.
    3. 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).
    4. M. Tadaros & A. Migdalas, 2022. "Bi- and multi-objective location routing problems: classification and literature review," Operational Research, Springer, vol. 22(5), pages 4641-4683, November.
    5. 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.

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