Research on decision-making optimization of emergency supply chain based on Markov chain and multi-objective model
Zhongguo Anquan Shengchan Kexue Jishu = Journal of Safety Science and Technology
; 18(7):19, 2022.
Article
in English
| ProQuest Central | ID: covidwho-1998560
ABSTRACT
In order to cope with the sudden disasters such as floods, COVID-19,etc.,a discrete time Markov chain and multi-objective programming model(DTMC-MOP) with the maximum supply satisfaction rate, the shortest supply time and the lowest supply cost was proposed to dynamically identify, analyze and respond to the emergency supply chain risk.The improved self-adaptive Non-dominated Sorting Genetic Algorithm-Ⅱ(NSGA-Ⅱ) was used to solve the optimization model, and the feasibility and effectiveness of the model were verified by testing and evaluation with standard test functions.Through the example analysis, the Pareto optimal front with higher precision and more uniform distribution was obtained.The results showed that the decision-maker could choose the appropriate emergency scheme based on the core objective of emergency management or different preferences.It provide a scientific method for the decision-making optimization of emergency supply chain, which has positive significance for ensuring the life safety of victims and maintaining the social harmony and stability.
Occupational Health And Safety; Chain dynamics; Markov chains; Cost analysis; Optimization; Genetic algorithms; Mathematical programming; Emergency management; Emergency response; COVID-19; Multiple objective analysis; Decision making; Sorting algorithms; Emergency preparedness; Supply chains; Optimization models
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Collection:
Databases of international organizations
Database:
ProQuest Central
Language:
English
Journal:
Zhongguo Anquan Shengchan Kexue Jishu = Journal of Safety Science and Technology
Year:
2022
Document Type:
Article
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