A possibilistic-robust-fuzzy programming model for designing a game theory based blood supply chain network
•Considering a competitive game for the problem of plasma collection in the context of the outbreak of COVID-19.•Providing the types of donors containing: healed donors, healed donors along with side diseases and healthy donors.•Considering various types of advertisements including social networks,...
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| Veröffentlicht in: | Applied mathematical modelling Jg. 112; S. 282 - 303 |
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| Sprache: | Englisch |
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01.12.2022
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| ISSN: | 0307-904X, 0307-904X |
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| Abstract | •Considering a competitive game for the problem of plasma collection in the context of the outbreak of COVID-19.•Providing the types of donors containing: healed donors, healed donors along with side diseases and healthy donors.•Considering various types of advertisements including social networks, TV ads, and banners to attract more donors.•Considering reserved donors and the possibility of donation during working and nonworking hours.•Suggesting a new mixed possibilistic-robust-fuzzy programming.
This paper presents a bi-level blood supply chain network under uncertainty during the COVID-19 pandemic outbreak using a Stackelberg game theory technique. A new two-phase bi-level mixed-integer linear programming model is developed in which the total costs are minimized and the utility of donors is maximized. To cope with the uncertain nature of some of the input parameters, a novel mixed possibilistic-robust-fuzzy programming approach is developed. The data from a real case study is utilized to show the applicability and efficiency of the proposed model. Finally, some sensitivity analyses are performed on the important parameters and some managerial insights are suggested. |
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| AbstractList | This paper presents a bi-level blood supply chain network under uncertainty during the COVID-19 pandemic outbreak using a Stackelberg game theory technique. A new two-phase bi-level mixed-integer linear programming model is developed in which the total costs are minimized and the utility of donors is maximized. To cope with the uncertain nature of some of the input parameters, a novel mixed possibilistic-robust-fuzzy programming approach is developed. The data from a real case study is utilized to show the applicability and efficiency of the proposed model. Finally, some sensitivity analyses are performed on the important parameters and some managerial insights are suggested.This paper presents a bi-level blood supply chain network under uncertainty during the COVID-19 pandemic outbreak using a Stackelberg game theory technique. A new two-phase bi-level mixed-integer linear programming model is developed in which the total costs are minimized and the utility of donors is maximized. To cope with the uncertain nature of some of the input parameters, a novel mixed possibilistic-robust-fuzzy programming approach is developed. The data from a real case study is utilized to show the applicability and efficiency of the proposed model. Finally, some sensitivity analyses are performed on the important parameters and some managerial insights are suggested. This paper presents a bi-level blood supply chain network under uncertainty during the COVID-19 pandemic outbreak using a Stackelberg game theory technique. A new two-phase bi-level mixed-integer linear programming model is developed in which the total costs are minimized and the utility of donors is maximized. To cope with the uncertain nature of some of the input parameters, a novel mixed possibilistic-robust-fuzzy programming approach is developed. The data from a real case study is utilized to show the applicability and efficiency of the proposed model. Finally, some sensitivity analyses are performed on the important parameters and some managerial insights are suggested. •Considering a competitive game for the problem of plasma collection in the context of the outbreak of COVID-19.•Providing the types of donors containing: healed donors, healed donors along with side diseases and healthy donors.•Considering various types of advertisements including social networks, TV ads, and banners to attract more donors.•Considering reserved donors and the possibility of donation during working and nonworking hours.•Suggesting a new mixed possibilistic-robust-fuzzy programming. This paper presents a bi-level blood supply chain network under uncertainty during the COVID-19 pandemic outbreak using a Stackelberg game theory technique. A new two-phase bi-level mixed-integer linear programming model is developed in which the total costs are minimized and the utility of donors is maximized. To cope with the uncertain nature of some of the input parameters, a novel mixed possibilistic-robust-fuzzy programming approach is developed. The data from a real case study is utilized to show the applicability and efficiency of the proposed model. Finally, some sensitivity analyses are performed on the important parameters and some managerial insights are suggested. |
| Author | Khanchehzarrin, Saeed Ghasemi, Peiman Goodarzian, Fariba Abraham, Ajith |
| Author_xml | – sequence: 1 givenname: Peiman orcidid: 0000-0002-1085-0776 surname: Ghasemi fullname: Ghasemi, Peiman email: Peiman.Ghasemi@gutech.edu.om organization: Department of Logistics, Tourism & Service Management, German University of Technology in Oman (GUtech), Muscat, Oman – sequence: 2 givenname: Fariba surname: Goodarzian fullname: Goodarzian, Fariba organization: Engineering Group, School of Engineering, University of Seville, Camino de los Descubrimientos s/n, Seville 41092, Spain – sequence: 3 givenname: Ajith surname: Abraham fullname: Abraham, Ajith organization: Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, 11, 3rd Street NW, P.O. Box 2259. Auburn, WA 98071, USA – sequence: 4 givenname: Saeed surname: Khanchehzarrin fullname: Khanchehzarrin, Saeed organization: Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran |
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| Keywords | Blood supply chain network COVID-19 pandemic Mixed possibilistic-robust-fuzzy programming Bi-level mixed-integer linear programming model Game theory |
| Language | English |
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| Snippet | •Considering a competitive game for the problem of plasma collection in the context of the outbreak of COVID-19.•Providing the types of donors containing:... This paper presents a bi-level blood supply chain network under uncertainty during the COVID-19 pandemic outbreak using a Stackelberg game theory technique. A... |
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| SubjectTerms | Bi-level mixed-integer linear programming model Blood supply chain network COVID-19 pandemic Game theory Mixed possibilistic-robust-fuzzy programming |
| Title | A possibilistic-robust-fuzzy programming model for designing a game theory based blood supply chain network |
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