Supply chain design to tackle coronavirus pandemic crisis by tourism management

Motevalli-Taher, Faezeh; Paydar, Mohammad Mahdi

doi:10.1016/j.asoc.2021.107217

Cited by 15 publications

(10 citation statements)

References 30 publications

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“…( 2021b ) Iran Ahmadzadeh and Shams ( 2021 ), Lak et al. ( 2021 ), Motevalli-Taher and Paydar ( 2021 ) India Maji et al. ( 2020 ), Thombre and Agarwal ( 2021 ) Canada Gargoum and Gargoum ( 2021 ) Denmark Ghayvat et al.…”

Section: Review Of the Literaturementioning

confidence: 99%

Data analytics during pandemics: a transportation and location planning perspective

2022

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The recent COVID-19 pandemic once again showed the value of harnessing reliable and timely data in fighting the disease. Obtained from multiple sources via different collection streams, an immense amount of data is processed to understand and predict the future state of the disease. Apart from predicting the spatio–temporal dynamics, it is used to foresee the changes in human mobility patterns and travel behaviors and understand the mobility and spread speed relationship. During this period, data-driven analytic approaches and Operations Research tools are widely used by scholars to prescribe emerging transportation and location planning problems to guide policy-makers in making effective decisions. In this study, we provide a review of studies which tackle transportation and location problems during the COVID-19 pandemic with a focus on data analytics. We discuss the major data collecting streams utilized during the pandemic era, highlight the importance of rapid and reliable data sharing, and give an overview of the challenges and limitations on the use of data.

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Section: Review Of the Literaturementioning

confidence: 99%

Data analytics during pandemics: a transportation and location planning perspective

2022

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“…To solve the problem, they applied a simulation approach with two optimization algorithms, Tabu Search (TS) and Simulated Annealing (SA). Motevalli-Taher and Paydar [56] developed a multi-objective mathematical model to reduce the outbreak of Corona Virus during Covid-19 pandemic. They modeled a mathematical model to reduce the number of patient from outside of city to prevent from the spread of virus to other cities.…”

Section: Criteria Referencesmentioning

confidence: 99%

Stochastic medical tourism problem with variable residence time considering gravity function

Kolaee¹,

Al-e-hashem²

2022

RAIRO-Oper. Res.

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Medical tourism is a recent term in healthcare logistics referring to travel of patients to receive health services and spending leisure time in a destination country. This transferring of patients leads to access high-quality health services which are cheaper than the original country of patients. During this travel, passengers who are the patients from another country, have this opportunity for complimentary entertainment packages (e.g., pleasure tours) in the aftercare period. As far as we know, the term of medical tourism is rarely studied in healthcare logistics and such services are highly important for developing countries. Such facts motivate us to develop a practical optimization model for the Medical Tour Centers (MTCs) for allocation of patients to hospitals in proper time and creation of memorable aftercare time for them. In this regard, the main aim of the proposed model is to maximize the total profit of MTCs through optimal allocation of patients to hospitals while considering an aftercare tour for the passengers. To make the proposed model more realistic, the optimal residence time in attractive places is simulated by a time-dependent gravity function. To address the uncertainty of medical tourism problem, a scenario-based two-stage stochastic optimization approach is extended to encounter different sources of uncertainty existing in surgical success, medical time, restoration restrictions, and the attraction of tourist places. Another novelty of this work is to propose an innovative hybrid meta-heuristic for large-scale instances, which is a combination of Progressive Hedging Algorithm (PHA) and Genetic Algorithm (GA). The model is analyzed by different test problems for small, medium, and large-scale instances where the hybrid meta-heuristic algorithm could solve them with an average gap of 3.4% in comparison with the commercial solver. The results revealed the importance of tourist opinion and public preferences in medical and pleasure tours, respectively, to improve the economic growth in this sector in developing countries.

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“…Regarding the pandemic disruptions in the SC sector and mitigating severe and harmful impacts on different supply chains, researchers and scholars sought the presence of supply chains that can cope with the unpleasant troubles and problems in this field. As we elaborately discuss recent studies in the supply chain in following, they encompass a variety of subjects such as supply chain design [21] , [22] , forecasting and planning [23] , supply management [24] , [25] , transportation and logistics management [26] , [27] .…”

Section: Literature Reviewmentioning

confidence: 99%

Disaster relief supply chain design for personal protection equipment during the COVID-19 pandemic

Mosallanezhad

Chouhan

Paydar

et al. 2021

Applied Soft Computing

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The global epidemic caused by novel coronavirus continues to be a crisis in the world and a matter of concern. The way the epidemic has wreaked havoc on the international level has become difficult for the healthcare systems to supply adequately personal protection equipment for medical personnel all over the globe. In this paper, considering the COVID-19 outbreak, a multi-objective, multi-product, and multi-period model for the personal protection equipment demands satisfaction aiming to optimize total cost and shortage, simultaneously, is developed. The model is embedded with instances and validated by both modern and classic multi-objective metaheuristic algorithms. Moreover, the Taguchi method is exploited to set the metaheuristic into their best performances by finding their parameters’ optimum level. Furthermore, fifteen test examples are designed to prove the established PPE supply chain model and tuned algorithms’ applicability. Among the test examples, one is related to a real case study in Iran. Finally, metaheuristics are evaluated by a series of related metrics through different statistical analyses. It can be concluded from the obtained results that solution methods are practical and valuable to achieve the efficient shortage level and cost.

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Supply chain design to tackle coronavirus pandemic crisis by tourism management

Cited by 15 publications

References 30 publications

Data analytics during pandemics: a transportation and location planning perspective

Data analytics during pandemics: a transportation and location planning perspective

Stochastic medical tourism problem with variable residence time considering gravity function

Disaster relief supply chain design for personal protection equipment during the COVID-19 pandemic

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