A review of key planning and scheduling in the rail industry in Europe and UK

Planning and scheduling activities within the rail industry have benefited from developments in computer-based simulation and modelling techniques over the last 25 years. Increasingly, the use of computational intelligence in such tasks is featuring more heavily in research publications. This paper examines a number of common rail-based planning and scheduling activities and how they benefit from five broad technology approaches. Summary tables of papers are provided relating to rail planning and scheduling activities and to the use of expert and decision systems in the rail industry.EPSR

Evaluation of using Swarm intelligence to produce facility layout solutions.

The facility layout problem is a combinatorial optimization problem that involves determining the location and shape of various departments within a facility based on inter-department volume and distance measures. An optimal solution to the problem will yield the most efficient layout based on the measures. The application of Particle Swarm Optimization (PSO) was recently proposed as an approach to solving the facility layout problem. With PSO, potential solutions are produced by dividing departments into swarms of Self-Organizing Tiles (SOT). By following a set of simple behavioral rules based on social information gathered from the environment, the tiles cooperate to produce solutions in a very short amount of time. Initial results provided improvements over CRAFT, one of the primary methods currently used for facility layout. The main contribution of this thesis work entails evaluating the use of swarm intelligence to produce optimal facility layouts as well as the use of shape measures to assess the quality of produced layouts. The major achievement of this thesis is the design and implementation of a tool that could produce facility layout solutions using Self- Organizing Tiles (SOT). This thesis advances the swarm paradigm by introducing alternative pathways for achieving contiguity of departments. This thesis utilizes the tool to examine the convergence of SOT on an enumerated optimum for a layout dataset, which requires the exhaustive evaluation of all permutations of a grid layout. The tool was also used to examine the effect of granularity on the ability of SOT to converge on facility layout solutions. A shape metric was utilized as a means of evaluating the quality of produced solutions based on the regularity of the shape of departments, and found that SOT produces fairly regular layouts when granularized to nine tiles per department. Finally, SOT was compared with other algorithms the experimental results revealed that SOT provided minor improvements over currently used methods

Scale-Invariant Specifications for Human-Swarm Systems

We present a method for controlling a swarm using its spectral decomposition -- that is, by describing the set of trajectories of a swarm in terms of a spatial distribution throughout the operational domain -- guaranteeing scale invariance with respect to the number of agents both for computation and for the operator tasked with controlling the swarm. We use ergodic control, decentralized across the network, for implementation. In the DARPA OFFSET program field setting, we test this interface design for the operator using the STOMP interface -- the same interface used by Raytheon BBN throughout the duration of the OFFSET program. In these tests, we demonstrate that our approach is scale-invariant -- the user specification does not depend on the number of agents; it is persistent -- the specification remains active until the user specifies a new command; and it is real-time -- the user can interact with and interrupt the swarm at any time. Moreover, we show that the spectral/ergodic specification of swarm behavior degrades gracefully as the number of agents goes down, enabling the operator to maintain the same approach as agents become disabled or are added to the network. We demonstrate the scale-invariance and dynamic response of our system in a field relevant simulator on a variety of tactical scenarios with up to 50 agents. We also demonstrate the dynamic response of our system in the field with a smaller team of agents. Lastly, we make the code for our system available.Comment: Journal of Field Robotics, Accepted for Publication. 25 page

Trajectory data mining: A review of methods and applications

The increasing use of location-aware devices has led to an increasing availability of trajectory data. As a result, researchers devoted their efforts to developing analysis methods including different data mining methods for trajectories. However, the research in this direction has so far produced mostly isolated studies and we still lack an integrated view of problems in applications of trajectory mining that were solved, the methods used to solve them, and applications using the obtained solutions. In this paper, we first discuss generic methods of trajectory mining and the relationships between them. Then, we discuss and classify application problems that were solved using trajectory data and relate them to the generic mining methods that were used and real world applications based on them. We classify trajectory-mining application problems under major problem groups based on how they are related. This classification of problems can guide researchers in identifying new application problems. The relationships between the methods together with the association between the application problems and mining methods can help researchers in identifying gaps between methods and inspire them to develop new methods. This paper can also guide analysts in choosing a suitable method for a specific problem. The main contribution of this paper is to provide an integrated view relating applications of mining trajectory data and the methods used