How, When, &amp; Where temporary hospitals fit in turbulent times: A hybrid MADM optimization in the middle east

Yazdi, Amir Karbassi; Muneeb, Farhan Muhammad; Hanne, Thomas; Ali, Adnan

doi:10.1016/j.cie.2022.108761

Cited by 3 publications

(3 citation statements)

References 61 publications

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“…Yazdi et al [40] employed a hybrid method for ranking nine candidate sites for hospital site selection. They used BWM in combination with Pythagorean fuzzy numbers in order to determine the criteria weights, and used the Evaluation by an Area-based Method of Ranking (EAMR) for hospital candidate site ranking.…”

Section: Related Workmentioning

confidence: 99%

“…Year Location Applied Methods [40] 2023 Chile Delphi, BWM, and EAMR [46] 2022 Iran GIS, Fuzzy Logic, and AHP [26] 2022 Egypt GIS and AHP [4] 2022 Iran GIS, CRITIC, SE, SDT, and OWA [24] 2022 India GIS and AHP [42] 2021 Turkey GIS, fuzzy AHP, and TOPSIS [41] 2021 Turkey Delphi, BWM, and fuzzy TOPSIS [23] 2019 Turkey AHP [45] 2016 India fuzzy ELECTRE [44] 2010 China ANP and TOPSIS [43] 2009 Iran GIS and fuzzy AHP…”

Section: Referencementioning

confidence: 99%

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GIS-Enabled Multi-Criteria Assessment for Hospital Site Suitability: A Case Study of Tehran

Zandi,

Pahlavani,

Bigdeli

et al. 2024

Sustainability

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In developing countries, the interaction between rapid urban expansion and population growth brings forth a host of challenges, particularly concerning essential services like healthcare. While interest in site suitability analysis for identifying optimal hospital locations to ensure equitable and secure healthcare access is on the rise, the absence of a holistic study that encompasses social and environmental aspects in the assessment of hospital site suitability is evident. The objective of this research is to introduce a hybrid methodology that combines Geographic Information Systems (GIS) with Multi-Criteria Decision-Making (MCDM) weighting methods. This methodology aims to create hospital site suitability maps for districts 21 and 22 in Tehran, taking into account socio-environmental factors. In addition to the conventional Analytical Hierarchical Process (AHP) weighting method, this study employs two relatively less-explored methods, the Best-Worst Method (BWM) and Step-wise Weight Assessment Ratio Analysis (SWARA), to enhance the analysis of hospital site suitability. In the SWARA method, there are minimal variations in weights among criteria, indicating that all socio-environmental factors (e.g., distance from existing hospitals, distance from main roads, distance from green spaces) hold significant importance in the decision-making process. Additionally, the findings indicate that the western part of the study area is the most suitable location for the construction of a new hospital. To achieve the average hospital bed availability in Tehran, an additional 2206 beds are required in the studied area, in addition to the existing facilities. Considering the ongoing urban development, population growth, and the potential for natural disasters and epidemics, it becomes essential to enhance the healthcare system by increasing the number of hospitals and available hospital beds. The sensitivity analysis showed that GIS-based SWARA-WLC was the most suitable and stable model for determining hospital site suitability in the study area. This methodology can be adapted for use in other regions and further improved by incorporating additional criteria. In conclusion, the study recommended three specific alternative sites for establishing a new hospital in the study area.

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Section: Related Workmentioning

confidence: 99%

Section: Referencementioning

confidence: 99%

GIS-Enabled Multi-Criteria Assessment for Hospital Site Suitability: A Case Study of Tehran

Zandi,

Pahlavani,

Bigdeli

et al. 2024

Sustainability

View full text Add to dashboard Cite

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“…Globally, the unprecedented COVID-19 outbreak reinforced the critical importance of rapid development vs. survival for pharmaceutical companies and had a significant impact on the medical supply chain as well [32,33]. During the COVID-19 outbreak, Govindan et al [34] created a biobjective MILP model for managing medical waste to reduce the overall costs and dangers of the population's exposure to pollution.…”

Section: Literature Reviewmentioning

confidence: 99%

A Mathematical Optimization Model for the Pharmaceutical Waste Location‐Routing Problem Using Genetic Algorithm and Particle Swarm Optimization

Aghakhani,

Pourmand,

Zarreh

2023

Mathematical Problems in Engineering

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Pharmaceutical waste management is a significant concern that poses risks to human and environmental health. The ineffective management of expired and unused medications can harm individuals and communities. This study proposes a novel approach to address the issue of pharmaceutical waste management by developing a location-routing problem (LRP) model using mixed-integer linear programing (MILP) to optimize the collection and disposal of pharmaceutical waste. The proposed model aims to minimize transportation costs, construction of collection centers, disposal costs, and carbon dioxide emissions, making it a cost-effective and environmentally sustainable approach to managing pharmaceutical waste. Initially, the feasibility, validity, and efficiency of the proposed model are examined by solving the problem in the GAMS software using CPLEX solver for small-scale problems. Sensitivity analyses are conducted to ensure the accuracy, reliability, robustness, and usefulness of the mathematical model for decision-making. In view of the inherent computational complexity of the proposed model, which is classified as nondeterministic polynomial time-hard and poses considerable difficulties when exact solutions are sought for large-scale problems, the present study resorts to two metaheuristic algorithms, specifically particle swarm optimization (PSO) and genetic algorithm (GA), as a means minimizing the computational burden. The results indicate that GA outperforms PSO in terms of objective function and solution time, with an average improvement of approximately 1% and 20%, respectively. The proposed model and algorithms provide a comprehensive approach to addressing the critical issue of pharmaceutical waste management, benefiting the healthcare industry, and society as a whole.

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A framework to evaluate the temporary hospital locations in wake of COVID-19 pandemic: implications to healthcare operations

Patil,

Shardeo,

Dwivedi

et al. 2023

Oper Manag Res

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How, When, & Where temporary hospitals fit in turbulent times: A hybrid MADM optimization in the middle east

Cited by 3 publications

References 61 publications

GIS-Enabled Multi-Criteria Assessment for Hospital Site Suitability: A Case Study of Tehran

GIS-Enabled Multi-Criteria Assessment for Hospital Site Suitability: A Case Study of Tehran

A Mathematical Optimization Model for the Pharmaceutical Waste Location‐Routing Problem Using Genetic Algorithm and Particle Swarm Optimization

A framework to evaluate the temporary hospital locations in wake of COVID-19 pandemic: implications to healthcare operations

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