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A Review of the Use of Linear Programming to Optimize Diets, Nutritiously, Economically and Environmentally

Overview of attention for article published in Frontiers in Nutrition, June 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

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1 news outlet
policy
1 policy source
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5 X users
patent
1 patent

Citations

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87 Dimensions

Readers on

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237 Mendeley
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Title
A Review of the Use of Linear Programming to Optimize Diets, Nutritiously, Economically and Environmentally
Published in
Frontiers in Nutrition, June 2018
DOI 10.3389/fnut.2018.00048
Pubmed ID
Authors

Corné van Dooren

Abstract

The "Diet Problem" (the search of a low-cost diet that would meet the nutritional needs of a US Army soldier) is characterized by a long history, whereas most solutions for comparable diet problems were developed in 2000 or later, during which computers with large calculation capacities became widely available and linear programming (LP) tools were developed. Based on the selected literature (52 papers), LP can be applied to a variety of diet problems, from food aid, national food programmes, and dietary guidelines to individual issues. This review describes the developments in the search for constraints. After nutritional constraints, costs constraints, acceptability constraints and ecological constraints were introduced. The 12 studies that apply ecological constraints were analyzed and compared in detail. Most studies have used nutritional constraints and cost constraints in the analysis of dietary problems and solutions, but such research begin showing weaknesses under situations featuring a small number of food items and/or nutritional constraints. Introducing acceptability constraints is recommended, but no study has provided the ultimate solution to calculating acceptability. Future possibilities lie in finding LP solutions for diets by combining nutritional, costs, ecological and acceptability constraints. LP is an important tool for environmental optimization and shows considerable potential as an instrument for finding solutions to a variety of very complex diet problems.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 237 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 237 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 36 15%
Student > Bachelor 29 12%
Student > Ph. D. Student 28 12%
Researcher 19 8%
Other 9 4%
Other 27 11%
Unknown 89 38%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 14%
Nursing and Health Professions 19 8%
Medicine and Dentistry 14 6%
Engineering 12 5%
Mathematics 11 5%
Other 51 22%
Unknown 97 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 05 March 2024.
All research outputs
#1,969,641
of 25,508,813 outputs
Outputs from Frontiers in Nutrition
#848
of 6,867 outputs
Outputs of similar age
#40,174
of 341,768 outputs
Outputs of similar age from Frontiers in Nutrition
#12
of 33 outputs
Altmetric has tracked 25,508,813 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,867 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.4. This one has done well, scoring higher than 87% of its peers.
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 341,768 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.