Good Laboratory Practice for optimization research
Journal of the Operational Research Society, ISSN: 1476-9360, Vol: 67, Issue: 4, Page: 676-689
2016
- 61Citations
- 86Usage
- 124Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Good Laboratory Practice has been a part of non-clinical research for over 40 years. Optimization Research, despite having many papers discussing standards being published over the same period of time, has yet to embrace standards that underpin its research. In this paper we argue the need to adopt standards in optimization research. Building on previous papers, many of which have suggested that the optimization research community should adopt certain standards, we suggest a concrete set of recommendations that the community should adopt. We also discuss how the proposals in this paper could be progressed.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84962258400&origin=inward; http://dx.doi.org/10.1057/jors.2015.77; https://www.tandfonline.com/doi/full/10.1057/jors.2015.77; https://www.tandfonline.com/doi/pdf/10.1057/jors.2015.77; http://link.springer.com/content/pdf/10.1057/jors.2015.77.pdf; http://link.springer.com/article/10.1057/jors.2015.77/fulltext.html; https://dx.doi.org/10.1057/jors.2015.77; https://ssrn.com/abstract=2753556; https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2753556; https://www.tandfonline.com/doi/abs/10.1057/jors.2015.77; https://link.springer.com/article/10.1057/jors.2015.77; https://link.springer.com/content/pdf/10.1057%2Fjors.2015.77.pdf; http://link.springer.com/content/pdf/10.1057/jors.2015.77; http://link.springer.com/10.1057/jors.2015.77
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