| Title |
Mathematical Programming Models for Determining the Optimal Location of Beehives
|
|---|---|
| Published in |
Bulletin of Mathematical Biology, March 2014
|
| DOI | 10.1007/s11538-014-9943-9 |
| Pubmed ID | |
| Authors |
Maica Krizna A. Gavina, Jomar F. Rabajante, Cleofas R. Cervancia |
| Abstract |
Farmers frequently decide where to locate the colonies of their domesticated eusocial bees, especially given the following mutually exclusive scenarios: (i) there are limited nectar and pollen sources within the vicinity of the apiary that cause competition among foragers; and (ii) there are fewer pollinators compared to the number of inflorescence that may lead to suboptimal pollination of crops. We hypothesize that optimally distributing the beehives in the apiary can help address the two scenarios stated above. In this paper, we develop quantitative models (specifically using linear programming) for addressing the two given scenarios. We formulate models involving the following factors: (i) fuzzy preference of the beekeeper; (ii) number of available colonies; (iii) unknown-but-bounded strength of colonies; (iv) probabilistic carrying capacity of the plant clusters; and (v) spatial orientation of the apiary. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Philippines | 3 | 43% |
| Spain | 1 | 14% |
| United Kingdom | 1 | 14% |
| France | 1 | 14% |
| Unknown | 1 | 14% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Scientists | 2 | 29% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Chile | 1 | 2% |
| New Zealand | 1 | 2% |
| Germany | 1 | 2% |
| Canada | 1 | 2% |
| Unknown | 41 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 20% |
| Student > Master | 8 | 18% |
| Student > Ph. D. Student | 7 | 16% |
| Student > Bachelor | 3 | 7% |
| Professor | 3 | 7% |
| Other | 6 | 13% |
| Unknown | 9 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 18 | 40% |
| Environmental Science | 5 | 11% |
| Mathematics | 5 | 11% |
| Chemical Engineering | 1 | 2% |
| Arts and Humanities | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 12 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 01 October 2018.
All research outputs
#4,179,920
of 25,255,356 outputs
Outputs from Bulletin of Mathematical Biology
#119
of 1,184 outputs
Outputs of similar age
#38,426
of 228,309 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#2
of 9 outputs
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