A Systematic Review of Linear Programming Techniques as Applied to Diet Optimisation and Opportunities for Improvement

Table 5

Summary of details retrieved from articles that did not specify minimisation or maximisation.

Reference	Objective function (s)	Decision variable (s)	Constraint (s)		Focus	Mathematical approach used
Pasic et al. [54]	Minimise variations from the defined nutrients (micro and macro), food cost	Food commodities		Recommended nutrient intake, upper limits of nutrients		Goal programming
Ferguson et al. [37]	Meet nutrient needs (while considering locally appropriate FBR that are low cost and can enhance nutrient adequacy)	Amount of food item		Energy content, minimum and maximum number of servings from food groups, grams of each food item	Find realistic food-based recommendations (FBRs) and ascertain how they could ensure intake adequacy for 12 nutrients	Linear programming (Optifood software)
McMahon et al. [28]	Minimise sodium intake while maintaining iodine intake	Reduction in sodium content in different foods		Nutrient intake (allowable levels, recommended dietary intake, upper limits)	To evaluate the intake of sodium and iodine against requirements and then model the possible impacts of salt-reduction strategies on estimated sodium and iodine intakes in indigenous Australian communities	Linear programming

FBRs—food-based recommendations.