Optimizing School Food Supply: Integrating Environmental, Health, Economic, and Cultural Dimensions of Diet Sustainability with Linear Programming

Abstract

There is great potential for reducing greenhouse gas emissions (GHGE) from public sector meals. This paper aimed to develop a strategy for reducing GHGE in the Swedish school food supply without compromising nutritional adequacy, affordability, and cultural acceptability. Amounts, prices and GHGE-values for all foods and drinks supplied to three schools over one year were gathered. The amounts were optimized by linear programming. Four nutritionally adequate models were developed: Model 1 minimized GHGE while constraining relative deviation (RD) from observed food supply; Model 2 minimized total RD while imposing stepwise GHGE reductions; Model 3 additionally constrained RD for individual foods to an upper and lower limit; and Model 4 further controlled how ratios between food groups could deviate. Models 1 and 2 reduced GHGE by up to 95% but omitted entire food categories or increased the supply of some individual foods by more than 800% and were deemed unfeasible. Model 3 reduced GHGE by up to 60%, excluded no foods, avoided high RDs of individual foods, but resulted in large changes in food group ratios. Model 4 limited changes in food group ratios but resulted in a higher number of foods deviating from the observed supply and limited the potential of reducing GHGE. Cost was reduced in almost all solutions. An omnivorous, nutritionally adequate, and affordable school food supply, with considerably lower GHGE is achievable with moderate changes to the observed food supply. Trade-offs will always have to be made between achieving GHGE reductions and preserving similarity to the current supply.

Successful Implementation of Climate-Friendly, Nutritious and Acceptable School Meals in Practice: the OPTIMAT™ Intervention Study

“…database is not open to the public and access was paid for by the research team. As described previously [22,28,29], all calculations of nutritional adequacy were based on the nutrient content of the edible proportions of prepared (cooked, boiled, oven baked etc.) foods, while the calculations for cost and CO2eq were done on the amount of raw food.…”

“…The baseline food list was optimized following a linear programming (LP) strategy described in detail elsewhere [22,29] and was implemented with the CBC (COIN-OR Branch and Cut Solver algorithm, part of the Excel® 2016 software add-in OpenSolver, V. 2.9.0 [30]. Briefly, LP aims to either minimize or maximize a linear objective function that is subjected to a set of linear constraints having to be met simultaneously.…”

“…Briefly, LP aims to either minimize or maximize a linear objective function that is subjected to a set of linear constraints having to be met simultaneously. As described previously [22,29], we chose to minimize the total relative deviation (TRD) from the baseline food supply across all 181 food items in an attempt to make the new menus as acceptable as possible. All applied nutritional and other food constraints are shown in Table 1.…”

“…This was not done in the aforementioned studies [20,21,41], although Benvenuti et al considered aspects such as frequency and composition of the meals, which to some extent parallels the contribution of the meal planner in this study. Other researchers have also emphasized the importance of considering cultural acceptability in the modelling of climate friendlier diets by minimizing the deviation from baseline diets as a proxy for acceptability [14,17,29,37,[42][43][44]. However, cultural acceptability of diets should ideally be regarded as a more complex matter, including aspects such as knowledge and preconceptions [45].…”

“…Optimization has been applied to model diets that are cost-effective, nutritionally adequate, and more climate friendly [12][13][14][15][16][17][18]. It has also been used to mathematically design nutritious and environmentally sustainable school meals [19][20][21]. Our research group has developed and tested a pragmatic approach for combining linear optimization with planning and serving of a new school lunch menu [22].…”