Featured research (2)
Natural disasters such as earthquakes can severely impact road networks. Depending on the disaster intensity and the size of the affected area, the network may be divided into multiple disconnected parts. In a disaster response context, decision-makers need to determine the roads that should be unblocked to facilitate relief activities such as search and rescue, evacuation, and distribution of emergency supplies. The multi-vehicle prize collecting arc routing for connectivity problem (KPC-ARCP) is a well-known problem dealing with such a scenario. A matheuristic to solve the KPC-ARCP was proposed in previous research, which tested instances with fewer than 400 vertices and 700 edges. However, it is unknown whether the matheuristic can handle larger instances. This article proposes a Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic with the hypothesis that GRASP is faster and can solve more extensive networks. Two sets of tests are performed on randomly generated instances with increasing size. The gap in the objective function values and the execution times of GRASP versus the matheuristic are compared. The results indicate that GRASP can achieve objective function values as good as the matheuristic and is significantly faster depending on the parameter settings.
Even though validation is an important concept in safety research, there is comparatively little empirical research on validating specific safety assessment, assurance, and ensurance activities. Focusing on model-based safety analysis, scant work exists to define approaches to assess a model’s adequacy for its intended use. Rooted in a wider concern for evidence-based safety practices, this paper intends to provide an understanding of the extent of this problem of lack of validation to establish a baseline for future developments. The state of the practice in validation of model-based safety analysis in socio-technical systems is analyzed through an empirical study of relevant published articles in the Safety Science journal spanning a decade (2010–2019). A representative sample is first selected using the PRISMA protocol. Subsequently, various questions concerning validation are answered to gain empirical insights into the extent, trends, and patterns of validation in this literature on model-based safety analysis. The results indicate that no temporal trends are detected in the ratio of articles in which models are validated compared to the total number of papers published. Furthermore, validation has no clear correlation with the specific model type, safety-related concept, different system life cycle stages, industries, or with the countries from which articles originate. Furthermore, a wide variety of terminology for validation is observed in the studied articles. The results suggest that the safety science field concerned with developing and applying models in safety analyses would benefit from an increased focus on validation. Several directions for future work are discussed.
- Department of Industrial Engineering
About Floris Goerlandt
- I obtained a M.Sc. engineering degree in Marine Technology (Ghent University, Belgium), a M.Sc. degree in Maritime Sciences (Antwerp University, Belgium) and a D.Sc. degree in Maritime Risk and Safety (Aalto University, Finland). My current research interests and areas include: risk analysis and management, safety management, and safety engineering. In terms of applications, I focus on the maritime application area, especially shipping risks related to human safety and environmental impacts. Furthermore, I aim to make contributions to the general risk and safety research disciplines, focusing on themes such as uncertainty treatment and validation.