Optimal Scheduling of COVID-19 Pandemic Supply Disruptions Under Uncertainty
Ieee Access
; 10:114374-114392, 2022.
Article
in English
| Web of Science | ID: covidwho-2123159
ABSTRACT
With the outbreak of COVID-19 pandemic, the problem of supply chain emergency scheduling has had a great influence on economic benefits of enterprises. The uncertainty of the COVID-19 pandemic and uncertainty of supply chain have made the problem of emergency scheduling more complicated. In this study, a multiobjective multiperiod mixed-integer programming optimization model was developed, in which two conflicting benefit factors, cost and service level were taken as the optimization target of the model. Cost and service level were normalized, and the weighted sum was taken as the objective function, which transformed the problem into a multiperiod nonlinear one. Two algorithms of Bi-level Modified Hybrid Genetic Algorithm (BMHGA) and Bi-level Hybrid Genetic Algorithm (BHGA) were designed to solve the model. Three emergency strategies have been proposed, including enabling alternative suppliers, repairing failure nodes and enabling internal suppliers' flexibility. The parameter of disruption scenario and its solution method were designed. Finally, the practicability of the proposed model and algorithm was demonstrated through application to a case study of an electronics supply chain. The results indicated that the optimal solution of two algorithms was between 2%-5%, and BMHGA could obtain a better optimal solution.
Supply chain management; COVID-19; Genetic algorithms; Pandemics; Mixed; integer linear programming; Job shop scheduling; Production facilities; A multiobjective multiperiod mixed-integer programming optimization; model; supply chain emergency scheduling; uncertain supply disruptions; uncertain demand; COVID-19 pandemic; bi-level modified hybrid genetic; algorithm (BMHGA); bi-level hybrid genetic algorithm (BHGA); GENETIC ALGORITHM; CHAIN; RESILIENCE
Full text:
Available
Collection:
Databases of international organizations
Database:
Web of Science
Language:
English
Journal:
Ieee Access
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS