| Title |
How to Escape Local Optima in Black Box Optimisation: When Non-elitism Outperforms Elitism
|
|---|---|
| Published in |
Algorithmica, September 2017
|
| DOI | 10.1007/s00453-017-0369-2 |
| Pubmed ID | |
| Authors |
Pietro S. Oliveto, Tiago Paixão, Jorge Pérez Heredia, Dirk Sudholt, Barbora Trubenová |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 29% |
| Researcher | 4 | 19% |
| Lecturer > Senior Lecturer | 1 | 5% |
| Student > Bachelor | 1 | 5% |
| Lecturer | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 6 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 24% |
| Engineering | 3 | 14% |
| Agricultural and Biological Sciences | 2 | 10% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Business, Management and Accounting | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 7 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 14 September 2017.
All research outputs
#13,569,135
of 23,001,641 outputs
Outputs from Algorithmica
#319
of 418 outputs
Outputs of similar age
#159,789
of 315,598 outputs
Outputs of similar age from Algorithmica
#2
of 2 outputs
Altmetric has tracked 23,001,641 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 418 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 23rd percentile – i.e., 23% 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 315,598 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.