Our research projects focus on decision making in the domain of agrifood and biobased supply chain. Central in these projects is the increasing complexity and uncertainty, as well as the specific characteristics of our domain. Our work supports organisations in
achieving robust performance, including the trade-offs between costs, service, quality and sustainability.
We have the following three main objectives
- To identify, analyse and understand developments in the life sciences (with emphasis on sustainability, technology and quality management) that put new requirements on logistics concepts and decision support models in the specific domains;
- To contribute to further developing innovative and sustainable logistics concepts and models given the continuous changes in the environment;
- To further develop dedicated decision support models and tools that are able to deal with the specific characteristics and the increased complexity and uncertainty of the given domains, and enable the assessment and application of the newly developed concepts.
Our contributions primarily take the form of publications of the developed innovative concepts as well as of the concrete models and algorithms. The conceptual output is underpinned and clarified by empirical experiments with the implemented optimisation and simulation models, often conducted in collaboration with practice.
Central in the problem characteristics of our research projects is increasing decision making complexity, dynamics and uncertainty whilst dealing with the specific characteristics of our domain. Organisations are striving for robust performances, not only on costs but also regarding the trade-off between product availability, product quality and supply chain sustainability. We aim to design robust agrifood supply chain networks with emphasis on logistics network design and management. Essential is a multidisciplinary research approach that combines advances in the fields of Logistics Management and Operations Research with expertise (methods, models and views) from typical Wageningen University & Research domains (e.g. food sciences, plant sciences, environmental sciences) and advances in technology (such as ICT and process technology) (Figure 1). Our research can be summarised as model-based design of logistics systems in agribusiness and food supply chains. It has three research themes.
Theme 1. Quality Controlled Logistics (QCL)
Environmental conditions have a strong impact on freshness and shelf-life of perishable produce. New technological developments make it possible to influence product quality changes during its travel through the chain and predictive quality decay models enable managers to predict the quality of products. In this theme we develop dedicated transport, production planning and inventory control concepts and models to the management of perishable goods flows using advanced product quality information in the decision process. The objective is to minimize food losses and maximize total value generated (at lowest cost) by delivering the right volume of the right product qualities to the best customers at the right time at the best place.
Theme 2. Sustainable Food Supply Chain Management
Sustainable Supply Chain Management (SSCM) is a rather new phenomenon in the Management Science and OR literature. A “sustainable” supply chain is a supply chain designed with the triple-bottom-line (people, planet, profit) in mind. In this theme we develop sustainable logistics management concepts and decision support models for the various stakeholders in the supply chain. For food supply chains the main attributes for sustainability are: prevention/reduction of spoilage (linking to theme 1), reuse/recycling of packaging waste, replacement of transport modalities (multi-modal transportation) and fuels (biobased energy). In order to capture the trade-offs between the logistics network costs and its respective environmental footprint for the decision makers, optimization of both objectives simultaneously is essential.
Theme 3. Efficient modelling and algorithms for Decision Support Models
It is clear that in themes 1 and 2 choosing the right activities in modelling specific logistic networks is crucial. The combinatorial and multi-objective nature of designing sustainable and QCL networks requires, besides smart algorithms, parsimonious models in order to keep the problem CPU-time tractable, without losing its explanatory power. Solving complex models often requires new or adapted ways of mathematical modelling or automated reasoning. Designing efficient algorithms to solve the complex models using sophisticated mathematical methods contributes to the knowledge of mathematical programming. Within this theme research is conducted on specific OR models and algorithms to support decision making on the themes mentioned before. The group not only focuses on how to get practical model implementations at work, but also investigates for which cases more standard algorithms can be used. Simulation of dynamic models is used for obtaining insight, but the major challenge is to combine optimisation with simulation to obtain better decisions.