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

Nikzamir, Mohammad; Baradaran, Vahid

doi:10.1016/j.tre.2020.102060

Cited by 34 publications

(15 citation statements)

References 55 publications

(82 reference statements)

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“…During the COVID-19 pandemic, several articles have been published considering its consequences on supply chains (e.g. Govindan et al, 2020;Nikzamir & Baradaran, 2020). However, we found no research that designs a viable healthcare supply chain network that effectively works in both pandemic and normal statuses.…”

Section: Contributions Of This Studymentioning

confidence: 69%

Viable healthcare supply chain network design for a pandemic

et al. 2022

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The recent COVID-19 pandemic revealed that healthcare networks must have a flexible and effective structure. In this study, we develop a viable healthcare network design for a pandemic using a multi-stage stochastic approach. We propose a multi-level network that includes health centers, computed tomography scan centers, hospitals, and clinics. Patients have conditions to returning to normal life or quarantining at home. Three objectives are defined: maximizing the probability of patient recovery, minimizing the costs of all centers in the network, and minimizing the Coronavirus death rate. We investigate a real case study in Iran to demonstrate the model’s applicability. Finally, we compare the healthcare supply chain network design in a pandemic with a normal situation to advise how the network can continue to remain viable.

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Section: Contributions Of This Studymentioning

confidence: 69%

Viable healthcare supply chain network design for a pandemic

et al. 2022

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“…The model was validated by using a case study from Iran and demonstrated a trade-off between objectives for better managing waste flows. Nikzamir and Baradaran (2020) presented a bi-objective model considering costs and emissions of contamination that could be intensified during the COVID-19 outbreak. They modeled the transferring time between nodes as random variables and used a meta -heuristic algorithm for solving that complex model.…”

Section: Literature Reviewmentioning

confidence: 99%

Medical waste management during coronavirus disease 2019 (COVID-19) outbreak: A mathematical programming model

Govindan

Nasr

Mostafazadeh

et al. 2021

Computers & Industrial Engineering

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Municipal solid waste (MSW) directly impacts community health and environmental degradation; therefore, the management of MSW is crucial. Medical waste is a specific type of MSW which is generally divided into two categories: infectious and non-infectious. Wastes generated by coronavirus disease 2019 (COVID-19) are classified among infectious medical wastes; moreover, these wastes are hazardous because they threaten the environment and living organisms if they are not appropriately managed. This paper develops a bi-objective mixed-integer linear programming model for medical waste management during the COVID-19 outbreak. The proposed model minimizes the total costs and risks, simultaneously, of the population’s exposure to pollution. This paper considers some realistic assumptions for the first time, including location-routing problem, time window-based green vehicle routing problem, vehicles scheduling, vehicles failure, split delivery, population risk, and load-dependent fuel consumption to manage both infectious and non-infectious medical waste. We apply a fuzzy goal programming approach for solving the proposed bi-objective model, and the efficiency of the proposed model and solution approach is assessed using data related to 13 nodes of medical waste production in a location west of Tehran.

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“…They contribute to the literature by incorporating into the model the fuel consumption and carbon dioxide emissions along the collection routes. Nikzamir and Baradaran [ 38 ] develop a mixed-integer nonlinear programming (MINLP) formulation for healthcare waste location and routing problem. The model includes stochastic transfer times between healthcare and treatment centers and emission of contamination.…”

Section: Literature Surveymentioning

confidence: 99%

Bi-Objective Adaptive Large Neighborhood Search Algorithm for the Healthcare Waste Periodic Location Inventory Routing Problem

Aydemir-Karadag

2021

Arab J Sci Eng

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There has been an unexpected increase in the amount of healthcare waste during the COVID-19 pandemic. Managing healthcare waste is vital, as improper practices in the waste system can lead to the further spread of the virus. To develop effective and sustainable waste management systems, decisions in all processes from the source of the waste to its disposal should be evaluated together. Strategic decisions involve locating waste processing centers, while operational decisions deal with waste collection. Although the periodic collection of waste is used in practice, it has not been studied in the relevant literature. This paper integrates the periodic inventory routing problem with location decisions for designing healthcare waste management systems and presents a bi-objective mixed-integer nonlinear programming model that minimizes operating costs and risk simultaneously. Due to the complexity of the problem, a two-step approach is proposed. The first stage provides a mixed-integer linear model that generates visiting schedules to source nodes. The second stage offers a Bi-Objective Adaptive Large Neighborhood Search Algorithm (BOALNS) that processes the remaining decisions considered in the problem. The performance of the algorithm is tested on several hypothetical problem instances. Computational analyses are conducted by comparing BOALNS with its other two versions, Adaptive Large Neighborhood Search Algorithm and Bi-Objective Large Neighborhood Search Algorithm (BOLNS). The computational experiments demonstrate that our proposed algorithm is superior to these algorithms in several performance evaluation metrics. Also, it is observed that the adaptive search engine increases the capability of BOALNS to achieve high-quality Pareto-optimal solutions.

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

Cited by 34 publications

References 55 publications

Viable healthcare supply chain network design for a pandemic

Viable healthcare supply chain network design for a pandemic

Medical waste management during coronavirus disease 2019 (COVID-19) outbreak: A mathematical programming model

Bi-Objective Adaptive Large Neighborhood Search Algorithm for the Healthcare Waste Periodic Location Inventory Routing Problem

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