G.D.H. Claassen

An application of Special Ordered Sets to a periodic milk collection problem

We present an OR-based approach to support a milk collection problem in a special branch of dairy industry. The annual growth of the sector and the continuous imbalance between milk supply and demand, has urged the sector to look for a different approach to their daily milk collection problem. Specific details of the problem environment (i.e., the continuous production on supply level and the delivery conditions on demand level) gave rise to choose for a short- to medium-term planning approach. The proposed decision support system has to be considered as an efficient tool for generating stable milk collection plans which in turn also serves as an effective starting point for the vehicle routing problem. From a computational point of view it turned out that the application of Special Ordered Sets type 1 (SOS1) was very useful. Although it appears from literature that the computational advantage of SOS1 is restricted to supplementary model conditions, this study shows that these conditions are not necessarily needed.

Decision Science : theory and applications

Decision science is the discipline that is concerned with the development and applications of quantitative methods and techniques to support decision making processes. This extensively revised edition of two former versions of the book discusses the general principles and often used optimisation techniques such as linear programming, integer programming, dynamic programming, non-linear programming, network theory, simulation and stochastic programming. This book aims to fill in the gap between theory and practice. It discusses the theoretical background of important quantitative methods and techniques as well as how they can be applied to practical decision making problems. Therefore, the modeling process is illustrated with examples of firms, consumers, governments and other non-profit organisations in agriculture related sectors. The authors have used their vast didactical experience to find a proper balance between mathematical exactness, knowledge and readability on the one hand and offer understanding, insights and applicability of the subjects on the other hand. The book is therefore an essential asset in introductory courses on decision science in undergraduate, postgraduate and research programmes.

Compromise programming: Non-interactive calibration of utility-based metrics

Utility functions have been used widely to support multi-objective decision-making. Expansion of a general additive utility function around the ideal results in a composite linear-quadratic metric of a compromise programming problem. Determining the unknown parameters of the composite linear-quadratic metric requires substantial interaction with the decision maker who might not always be available or capable to participate in such a process. We propose a non-interactive method that uses information on observed attribute levels to obtain the unknown parameters of the composite linear-quadratic metric and enables forecasting and scenario analysis. The method is illustrated with a small scale numerical example.

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.

“Combining equity and utilitarianism”—additional insights into a novel approach

Recently, a novel approach (to be referred to as CEU) was introduced for the frequently arising problem of combining the conflicting criteria of equity and utilitarianism. This paper provides additional insights into CEU and assesses its added value for practice by comparing it with a commonly used extended goal programming (EGP) approach. The comparison comprises the way of balancing equity and utilitarianism, the number and spacing of solutions, discrete versus continuous nature, method-specific parameters, distance to the Pareto front, and computational effort. CEU balances between equity and utilitarianism in a way that is basically different from using a convex combination of these two criteria. Moreover, CEUs parameter has an intuitive interpretation. The set of solutions generated by CEU is smaller and more widely spaced than EGPs set of solutions, which can be an advantage for the decision maker. CEU generates solutions on the Pareto front of the decision makers n-criteria problem. However, CEUs way of balancing equity and utilitarianism causes a (small) distance to the Pareto front of the associated bicriteria problem on the aggregate criteria. Reporting this distance will support the decision maker to assess whether the achieved balance is worth its price. Using CEU may require a larger computational effort than using EGP.

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.