Multi-objective optimization for eco-efficient food supply chains

Until recently, food production focused mainly on delivering high-quality products at low cost and little attention was paid to environmental impact and depletion of natural resources. As a result of the growing awareness of climate change, shrinking resources, and increasing world population, this trend is changing. A major concern in Food Supply Chains (FSCs) is food waste. To remain competitive, FSCs are challenged to adopt new technologies that reduce or valorize food waste. These technologies can contribute to maintaining or increasing economic output and concurrently reduce the environmental impact of current operations, i.e. achieving what has been defined as eco-efficiency. Designing eco-efficient supply chains requires complex decision support models that can deal with multiple dimensions of sustainability while taking into account the specific characteristics of products and their supply chain. Multi-Criteria Decision Making (MCDM), a research field within Operations Research, is particularly suitable to support decision making when multiple and (mostly) conflicting criteria are involved. In this research, multi-objective optimization was used to quantify trade-offs between conflicting objectives and derive eco-efficient solutions, i.e. solutions in which environmental performance can only be improved at higher cost. The overall objective of this thesis was to support decision making in FSCs by developing dedicated decision support models to optimize and re-design FSCs by balancing the economic and environmental criteria. The emphasis is directed towards valorization of product flows by means of closing loops and waste management at a chain level. In line with this overall objective, four research questions were defined, which are addressed in Chapters 2 to 5. In Chapter 2, the use of MCDM approaches for designing Green Supply Chains (GSCs) is reviewed; GSCs extend traditional supply chains to include activities that minimize the environmental impact of a product throughout its life cycle. A conceptual framework was developed to find relevant publications and categorize papers with respect to decision problems, indicators, and MCDM approaches. The analysis shows that the use of MCDM approaches for designing GSCs is a new but emerging research field. Most publications focus on production and distribution problems, and there are only a few inventory models with environmental considerations. Most papers assume all data to be deterministic. Moreover, little attention has been given to minimization of waste in studies on FSCs, and numerous indicators are used to account for eco-efficiency, indicating the lack of standards. Chapter 2, therefore, identifies the need for more multi-criteria models for real-life GSCs, especially with respect to supply chains dealing with food production, and with inclusion of uncertainty in parameters. Environmental concerns and scarcity of resources encourage decision makers in supply chains to consider alternative production options that include preventing the production of waste streams and simultaneously reusing and recycling waste materials. Until now, quantitative modelling approaches on closing loops in FSCs have been rare in the literature. The aim of Chapter 3 was to develop a mathematical model that can be used for quantitative assessment of alternative production options associated with different ways of dealing with waste in FSCs, i.e. prevention, recycling, and disposal of food waste. A multi-objective mixed integer linear programming model was developed to derive a set of eco-efficient solutions corresponding to production planning decisions. The environmental performance of the chain is expressed by an indicator based on exergy analysis, which has the potential to capture other commonly used indicators, such as energy consumption, fuel consumption, and waste generation, in a single value. This simplifies the calculation of the eco-efficient frontier and enables its intuitive graphical representation, which is much easier to communicate to the decision makers. The applicability of the model is demonstrated on a real-life industrial bread supply chain in the Netherlands. The results confirm the findings from the literature that prevention is the best waste management strategy from an environmental perspective. The advantages of using exergy as an indicator to capture the environmental performance is demonstrated by comparing the outcomes with other commonly used indicators of environmental performance. The potential of studying food production planning decision problems in a multi-objective context is illustrated and the applicability of the model in the assessment of alternative production options is demonstrated. In contrast to closed-loop studies in industry involving discrete parts, in FSCs the value of the final product usually cannot be regained. However, the components used for production, such as organic matter or a growing medium, can be recycled. The aim of Chapter 4 was to reveal the consequences of closing loops in a mushroom supply chain. A multi-objective mixed integer linear programming model was proposed to quantify trade-offs between economic and environmental indicators and to explore alternative recycling technologies quantitatively. The model was developed to re-design the logistical structure and close loops in the mushroom supply chain. It was found that adopting closing loop technologies in industrial mushroom production has the potential to increase the total profitability of the chain by almost 11% and improve the environmental performance by almost 28%. It is concluded that a comprehensive evaluation of recycling technologies and re-designing logistical structures requires quantitative tools that simultaneously optimize managerial decisions at strategic and tactical levels. Multi-objective optimization models are often developed under the assumption that all information required for model parameterization is known in advance. In practice, however, not all the required information is available in advance because of various sources of uncertainty in FSCs. In Chapter 5, a multi-objective two-stage stochastic programming model was proposed to analyse and evaluate the economic and environmental impacts to account for uncertainty in FSCs. A mushroom supply chain in the Netherlands is presented as an illustrative case study. Optimal production planning decisions calculated with a two-stage stochastic programming model are compared with the results of an equivalent deterministic model. It is demonstrated that taking uncertainty into account at the production planning phase in an FSC can bring substantial economic and environmental benefits. The research presented in this thesis contributes to the scientific literature on eco-efficient FSCs by providing decision support models for use by decision makers to assess alternative logistical structures and quantify the economic and environmental implications of closing loop technologies. This thesis shows that technological innovations, which allow for reuse and recycling of waste streams, have the potential to improve the economic and environmental performance of an FSC substantially. The case studies illustrate that it is worthwhile investing in research on technological innovations (and their development) for closing loops in FSCs. The greatest benefits are brought about by using materials to their full potential by valorizing waste streams as much as possible.