With the increasing size and frequency of mass events, the study of crowd disasters and the simulation of pedestrian flows have become important research areas. However, even successful modeling approaches such as those inspired by Newtonian force models are still not fully consistent with empirical observations and are sometimes hard to calibrate. Here, a cognitive science approach is proposed...

Abstract Recent works using deep learning to solve routing problems such as the traveling salesman problem (TSP) have focused on construction heuristics. Such approaches find good quality solutions but require additional procedures beam search and sampling improve achieve state-of-the-art performance. However, few studies improvement heuristics, where a given solution is improved until reaching...

We investigate the performance of five approaches to scheduling a Japanese printed wiring board manufacturer's drilling operation subject to uncertainty. We present and evaluate two optimization approaches against three dispatching heuristics in order to determine how five performance measures are impacted by various levels of processing time variability and equipment breakdowns.

In the context of Smart Grid applications, distributed control algorithms show advantageous properties over classical centralized approaches. Regarding their operation in a critical infrastructure, however, it is of utmost importance to validate the correct behavior of such approaches beforehand. In this paper, we give an overview on different aspects of evaluating Smart Grid applications, with...