A bi-level mathematical model for logistic management considering the evolutionary game with environmental feedbacks

被引:42
|
作者
Ghasemi, Peiman [1 ]
Goodarzian, Fariba [2 ]
Gunasekaran, Angappa [3 ]
Abraham, Ajith [2 ,4 ]
机构
[1] Islamic Azad Univ, Ind Engn, South Tehran Branch, Tehran, Iran
[2] Sci Network Innovat & Res Excellence, Machine Intelligence Res Labs MIR Labs, Auburn, DC USA
[3] Calif State Univ, Sch Business & Publ Adm, Bakersfield, CA USA
[4] Innopolis Univ, Ctr Artificial Intelligence, Innopolis, Russia
关键词
Evolutionary games; Environmental feedbacks; R-Interdiction Median Problem; Fortifier; Location-allocation-routing problems; NETWORK INTERDICTION; HUB INTERDICTION; PROTECTION; ALGORITHM; FACILITIES;
D O I
10.1108/IJLM-04-2021-0199
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Purpose This paper proposed a bi-level mathematical model for location, routing and allocation of medical centers to distribution depots during the COVID-19 pandemic outbreak. The developed model has two players including interdictor (COVID-19) and fortifier (government). Accordingly, the aim of the first player (COVID-19) is to maximize system costs and causing further damage to the system. The goal of the second player (government) is to minimize the costs of location, routing and allocation due to budget limitations. Design/methodology/approach The approach of evolutionary games with environmental feedbacks was used to develop the proposed model. Moreover, the game continues until the desired demand is satisfied. The Lagrangian relaxation method was applied to solve the proposed model. Findings Empirical results illustrate that with increasing demand, the values of the objective functions of the interdictor and fortifier models have increased. Also, with the raising fixed cost of the established depot, the values of the objective functions of the interdictor and fortifier models have raised. In this regard, the number of established depots in the second scenario (COVID-19 wave) is more than the first scenario (normal COVID-19 conditions). Research limitations/implications The results of the current research can be useful for hospitals, governments, Disaster Relief Organization, Red Crescent, the Ministry of Health, etc. One of the limitations of the research is the lack of access to accurate information about transportation costs. Moreover, in this study, only the information of drivers and experts about transportation costs has been considered. In order to implement the presented solution approach for the real case study, high RAM and CPU hardware facilities and software facilities are required, which are the limitations of the proposed paper. Originality/value The main contributions of the current research are considering evolutionary games with environmental feedbacks during the COVID-19 pandemic outbreak and location, routing and allocation of the medical centers to the distribution depots during the COVID-19 outbreak. A real case study is illustrated, where the Lagrangian relaxation method is employed to solve the problem.
引用
收藏
页码:1077 / 1100
页数:24
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