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Bilevel mixed-integer nonlinear programming for integrated scheduling in a supply chain network

Overview of attention for article published in Cluster Computing, March 2018
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Mentioned by

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1 Facebook page

Citations

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2 Dimensions

Readers on

mendeley
14 Mendeley
Title
Bilevel mixed-integer nonlinear programming for integrated scheduling in a supply chain network
Published in
Cluster Computing, March 2018
DOI 10.1007/s10586-018-2673-2
Authors

Jianchao Yang, Feng Guo, Li Luo, Xiaoming Ye

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 14%
Student > Ph. D. Student 2 14%
Student > Doctoral Student 1 7%
Professor 1 7%
Student > Bachelor 1 7%
Other 2 14%
Unknown 5 36%
Readers by discipline Count As %
Engineering 4 29%
Decision Sciences 1 7%
Mathematics 1 7%
Unknown 8 57%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 April 2018.
All research outputs
#20,478,782
of 23,039,416 outputs
Outputs from Cluster Computing
#255
of 276 outputs
Outputs of similar age
#291,346
of 329,982 outputs
Outputs of similar age from Cluster Computing
#19
of 21 outputs
Altmetric has tracked 23,039,416 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 276 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,982 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.