Author:
Zhou Yufeng,Cheng Jiahao,Wu Changzhi,Teo Kok Lay
Abstract
AbstractThe problem of blood transshipment and allocation in the context of the COVID-19 epidemic has many new characteristics, such as two-stage, trans-regional, and multi-modal transportation. Considering these new characteristics, we propose a novel multi-objective optimization model for the two-stage emergent blood transshipment-allocation. The objectives considered are to optimize the quality of transshipped blood, the satisfaction of blood demand, and the overall cost including shortage penalty. An improved integer encoded hybrid multi-objective whale optimization algorithm (MOWOA) with greedy rules is then designed to solve the model. Numerical experiments demonstrate that our two-stage model is superior to one-stage optimization methods on all objectives. The degree of improvement ranges from 0.69 to 66.26%.
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Engineering (miscellaneous),Information Systems,Artificial Intelligence
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