Designing healthier and acceptable diets using data envelopment analysis.

OBJECTIVE: The objective of this research is to propose methodology that can be used to benchmark current diets based on their nutrient intakes and to provide guidelines for improving less healthy diets in a way that is acceptable for the studied population. DESIGN: We discuss important limitations of current diet models that use optimisation techniques to design healthier and acceptable diets. We illustrate how data envelopment analysis could be used to overcome such limitations, and we describe mathematical models that can be used to calculate not only healthier but also acceptable diets. SETTING: We used data from the Nutrition Questionnaires plus dataset of habitual diets of a general population of adult men and women in The Netherlands (n 1735). PARTICIPANTS: Adult population. RESULTS: We calculated healthier diets with substantial higher intakes of protein, fibre, Fe, Ca, K, Mg and vitamins, and substantially lower intakes of Na, saturated fats and added sugars. The calculated diets are combinations of current diets of individuals that belong to the same age/gender group and comprise of food item intakes in proportions observed in the sample. CONCLUSIONS: The proposed methodology enables the benchmarking of existing diets and provides a framework for proposing healthier alternative diets that resemble the current diet in terms of foods intake as much as possible.

Modelling and evaluating municipal solid waste management strategies in a mega-city: the case of Ho Chi Minh City.

Ho Chi Minh City is a large city that will become a mega-city in the near future. The city struggles with a rapidly increasing flow of municipal solid waste and a foreseeable scarcity of land to continue landfilling, the main treatment of municipal solid waste up to now. Therefore, additional municipal solid waste treatment technologies are needed. The objective of this article is to support decision-making towards more sustainable and cost-effective municipal solid waste strategies in developing countries, in particular Vietnam. A quantitative decision support model is developed to optimise the distribution of municipal solid waste from population areas to treatment plants, the treatment technologies and their capacities for the near future given available infrastructure and cost factors.

Vehicle routing for the eco-efficient collection of household plastic waste.

Plastic waste is a special category of municipal solid waste. Plastic waste collection is featured with various alternatives of collection methods (curbside/drop-off) and separation methods (source-/post-separation). In the Netherlands, the collection routes of plastic waste are the same as those of other waste, although plastic is different than other waste in terms of volume to weight ratio. This paper aims for redesigning the collection routes and compares the collection options of plastic waste using eco-efficiency as performance indicator. Eco-efficiency concerns the trade-off between environmental impacts, social issues and costs. The collection problem is modeled as a vehicle routing problem. A tabu search heuristic is used to improve the routes. Collection alternatives are compared by a scenario study approach. Real distances between locations are calculated with MapPoint. The scenario study is conducted based on real case data of the Dutch municipality Wageningen. Scenarios are designed according to the collection alternatives with different assumptions in collection method, vehicle type, collection frequency and collection points, etc. Results show that the current collection routes can be improved in terms of eco-efficiency performance by using our method. The source-separation drop-off collection scenario has the best performance for plastic collection assuming householders take the waste to the drop-off points in a sustainable manner. The model also shows to be an efficient decision support tool to investigate the impacts of future changes such as alternative vehicle type and different response rates.