Wicked problems are a special subset of particularly complex issues that current problem-solving tools fail tofully address. Because of this deficiency, a new tool for evaluating and resolving wicked problems must be developed. Theories such as anti-positivism and systems thinking are explored in order to understand the nature of wicked problems, which are often defined by the involvement of multiple stakeholders as well as non-linear interrelations between various elements of the problem. Although traditional problem-solving methods are inadequate for wicked problems, there are certain tools that are more appropriate for handling such problems. These tools include the analytic hierarchy process, positional analysis, mess maps and heat maps. With their organized structures, visual languages and collaborative processes, these methods provide features that are well suited for tackling wicked problems. However, no single tool incorporates all of the necessary features. Therefore, a combination of the tools explored can yield a new and even more effective tool for wicked problems. This new tool, called STORM, is demonstrated through an evaluation of oil shale exploitation in Estonia. With Estonia currently dependent on energy from oil shale despite the environmental drawbacks, the situation is an ideal example of a wicked problem. The Estonian example shows how STORM can provide a greater understanding of wicked problems and allow resolutions to be negotiated. As sustainable development issues are usually considered to be wickedto sustainable development research.

The vehicle routing problem is an optimisation problem with a high computational complexity that can be solved using heuristics methods to achieve near-optimal solutions in a reasonable amount of time. The work done in this study aims to compare the execution time and distance of different routing engines when using VROOM, as well as evaluate different implementations of the k-means algorithm by looking at the rand- and adjusted rand index. The results show a difference in the distance and execution time depending on which routing engine is used and it is unclear if there is a difference in the k-means implementations. Investigating the cause behind the observed results would be interesting in future works.