Evidence map›Paper›PMID 36855682›Full record

ArticleComplex & intelligent systems2023

Multi-objective two-stage emergent blood transshipment-allocation in COVID-19 epidemic.

Yufeng Zhou, Jiahao Cheng, Changzhi Wu, Kok Lay Teo

Abstract read
In one paragraph

Article in Complex & intelligent systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yufeng ZhouResearch Center for Economy of Upper Reaches of the Yangtze River, Chongqing Technology and Business University, Chongqing, 400067 China.
Jiahao ChengSchool of Business Administration, Chongqing Technology and Business University, Chongqing, 400067 China.
Changzhi WuSchool of Management, Guangzhou University, Guangzhou, 510006 China.
Kok Lay TeoSchool of Mathematics, Sunway University, 47500 Selangor Darul Ehsan, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The 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%.

Indexed as

Blood shortageBlood supply chainBlood transshipmentCOVID-19MOWOA

Identifiers

PMID36855682
PMCPMC9950024

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.