Multi-objective decision-making for dietary assessment and advice

Unhealthy diets contribute substantially to the worldwide burden of non-communicable diseases, such as cardiovascular diseases, cancers, and diabetes. Globally, non-communicable diseases are the leading cause of death, and numbers are still rising, which makes healthy diets a global priority. In Nutrition Research, two fields are particularly relevant for formulating healthier diets: dietary assessment, which assesses food and nutrient intake in order to investigate the relation between diet and disease, and dietary advice, which translates food and nutrient recommendations into realistic food choices. Both fields face complex decision problems: which foods to include in dietary assessment or advice in order to pursue the multiple objectives of the researcher or fulfil the requirements of the consumer. This thesis connects the disciplines of Nutrition Research and Operations Research in order to contribute to formulating healthier diets. In the context of dietary assessment, the thesis proposes a MILP model for the selection of food items for food frequency questionnaires (a crucial tool in dietary assessment) that speeds up the selection process and increases standardisation, transparency, and reproducibility. An extension of this model gives rise to a 0-1 fractional programming problem with more than 200 fractional terms, of which in every feasible solution only a subset is actually defined. The thesis shows how this problem can be reformulated in order to eliminate the undefined fractional terms. The resulting MILP model can solved with standard software. In the context of dietary advice, the thesis proposes a diet model in which food and nutrient requirements are formulated via fuzzy sets. With this model, the impact of various achievement functions is demonstrated. The preference structures modelled via these achievement functions represent various ways in which multiple nutritional characteristics of a diet can be aggregated into an overall indicator for diet quality. Furthermore, for Operations Research the thesis provides new insights into a novel preference structure from literature, that combines equity and utilitarianism in a single model. Finally, the thesis presents conclusions of the research and a general discussion, which discusses, amongst others, the main modelling choices encountered when using MODM methods for optimising diet quality. Summarising, this thesis explores the use of MODM approaches to improve decision-making for dietary assessment and advice. It provides opportunities for better decision-making in research on dietary assessment and advice, and it contributes to model building and solving in Operations Research. Considering the added value for Nutrition Research and the new models and solutions generated, we conclude that the combination of both fields has resulted in synergy between Nutrition Research and Operations Research.</p

Data Envelopment Analysis of sustainability indicators of European agricultural systems at regional level

Assessing the sustainability of a regional agricultural system is complex, because in different decision-making contexts stakeholders can use different criteria and methodologies, thus arriving at different and contrasting judgments. One way of dealing with the complexity of measuring the concept of sustainability is to adopt a multidimensional perspective, which recognizes the presence of an economic dimension which requires feasibility, a social dimension which requires acceptability, and an environmental dimension which requires carrying capacity. Many approaches for measuring sustainability face the difficulty to reconcile this multidimensional perspective with the necessity to come up with a "synthetic" and one-dimensional assessment measure that could be used for both policy-making and methodological purposes. The goal of this paper is to contribute to the development of a methodological approach that can simplify the assessment procedure of sustainability of agricultural systems, while considering the multidimensional perspective. We used the three dimensions of sustainability to define two economic indicators, two social indicators, and four environmental indicators of sustainability. Then we used Data Envelopment Analysis (DEA) to partition 252 European agricultural regions into a subset of DEA-efficient regions and a subset of non-efficient regions under five scenarios. The scenarios reflect preferences with respect to the importance of the three dimensions of sustainability. Impact of model choices such as constant versus variable returns to scale, input versus output orientation, and balancing constraints is shown. The combination of multidimensional perspective and DEA allowed to operationalize the complex and sophisticated concept of sustainability. Applying DEA at the EU regional level enabled analysis of the heterogeneity of performances within each EU Member State and among them. This heterogeneity is a fundamental research topic in the domain of assessment of sustainability of agricultural systems. (C) 2013 Elsevier Ltd. All rights reserved

Data Envelopment Analysis of sustainability indicators of European agricultural systems at regional level

Assessing the sustainability of a regional agricultural system is complex, because in different decision-making contexts stakeholders can use different criteria and methodologies, thus arriving at different and contrasting judgments. One way of dealing with the complexity of measuring the concept of sustainability is to adopt a multidimensional perspective, which recognizes the presence of an economic dimension which requires feasibility, a social dimension which requires acceptability, and an environmental dimension which requires carrying capacity. Many approaches for measuring sustainability face the difficulty to reconcile this multidimensional perspective with the necessity to come up with a "synthetic" and one-dimensional assessment measure that could be used for both policy-making and methodological purposes. The goal of this paper is to contribute to the development of a methodological approach that can simplify the assessment procedure of sustainability of agricultural systems, while considering the multidimensional perspective. We used the three dimensions of sustainability to define two economic indicators, two social indicators, and four environmental indicators of sustainability. Then we used Data Envelopment Analysis (DEA) to partition 252 European agricultural regions into a subset of DEA-efficient regions and a subset of non-efficient regions under five scenarios. The scenarios reflect preferences with respect to the importance of the three dimensions of sustainability. Impact of model choices such as constant versus variable returns to scale, input versus output orientation, and balancing constraints is shown. The combination of multidimensional perspective and DEA allowed to operationalize the complex and sophisticated concept of sustainability. Applying DEA at the EU regional level enabled analysis of the heterogeneity of performances within each EU Member State and among them. This heterogeneity is a fundamental research topic in the domain of assessment of sustainability of agricultural systems. (C) 2013 Elsevier Ltd. All rights reserved

Diet models with linear Goal Programming: impact of achievement functions

Background/Objectives: Diet models based on goal programming (GP) are valuable tools in designing diets that comply with nutritional, palatability and cost constraints. Results derived from GP models are usually very sensitive to the type of achievement function that is chosen. This paper aims to provide a methodological insight into several achievement functions. It describes the extended GP (EGP) achievement function, which enables the decision maker to use either a MinSum achievement function (which minimizes the sum of the unwanted deviations) or a MinMax achievement function (which minimizes the largest unwanted deviation), or a compromise between both. An additional advantage of EGP models is that from one set of data and weights multiple solutions can be obtained. Subjects/Methods: We use small numerical examples to illustrate the ‘mechanics’ of achievement functions. Then, the EGP achievement function is demonstrated on a diet problem with 144 foods, 19 nutrients and several types of palatability constraints, in which the nutritional constraints are modeled with fuzzy sets. Results: Choice of achievement function affects the results of diet models. Conclusions: MinSum achievement functions can give rise to solutions that are sensitive to weight changes, and that pile all unwanted deviations on a limited number of nutritional constraints. MinMax achievement functions spread the unwanted deviations as evenly as possible, but may create many (small) deviations. EGP comprises both types of achievement functions, as well as compromises between them. It can thus, from one data set, find a range of solutions with various properties

General 0-1 fractional programming with conditional fractional terms for design of food frequency questionnaires

Optimising an important methodological tool in nutritional epidemiology gives rise to a general 0–1 fractional programming problem with more than 200 fractional terms. All fractional terms are conditional, i.e. in every feasible solution only a subset of the fractional terms is actually defined. Existing literature does not provide a solution method. We extend known reformulation approaches to reformulate the general 0–1 fractional programming problem such that it can be solved by standard MILP software. Practical instances were solved fast

Sustainable supply chain design in the food system with dietary considerations: A multi-objective analysis

Food is a vital component of everyday life, however current consumption and production patterns pose a threat to the environment and the food security of future generations. Thus, with environmental burdens becoming more apparent and rising societal awareness, it is time to reconsider dietary choices and the food system behind it. This paper presents a novel application of a network design problem, addressing sustainability issues in the context of the global food system. Taking into account several echelons and interlinkages between different food supply chains, the paper broadens the scope of the considered network and incorporates sourcing, processing and transportation decisions within a common framework. While minimising different environmental and economic objectives, the model aims to maintain a sufficient dietary intake level. Consumption decisions are incorporated in the model through different types of consumer demands. The problem is formulated based on linear programming and further analysis is carried out by applying the ϵ-constraint method and compromise programming. Investigating alternative production and consumption scenarios as well as trade-offs between the conflicting objectives, the study is illustrated based on a nutritional case study and underpinned by real-life LCA data. The findings of this research are manifold, highlighting the importance of considering consumption and production decisions in an integrated and global setting. Moreover, the choice of sustainability indicator plays a crucial role given the often conflicting nature of different sustainability aspects