Scheduling and Platforming Trains at Busy Complex Stations

We consider the problem of train planning or scheduling for large, busy, complex train stations, which are common in Europe and elsewhere, though not in North America. We develop the constraints and objectives for this problem, but these are too computationally complex to solve by standard combinatorial search or integer programming methods. Also, the problem is somewhat political in nature, that is, it does not have a clear objective function because it involves multiple train operators with conflicting interests. We therefore develop scheduling heuristics analogous to those successfully adopted by train planners using ''manual'' methods. We tested the model and algorithms by applying to a typical large station that exhibits most of the complexities found in practice. The results compare well with those found by traditional methods, and take account of cost and preference trade-offs not handled by those methods. With successive refinements, the algorithm eventually took only a few seconds to run, the time depending on the version of the algorithm and the scheduling problem. The scheduling models and algorithms developed and tested here can be used on their own, or as key components for a more general system for train scheduling for a rail line or network.Train scheduling for a busy station includes ensuring that there are no conflicts between several hundred trains per day going in and out of the station on intersecting paths from multiple in-lines and out-lines to multiple platforms, while ensuring that each train is allowed at least its minimum required headways, dwell time, turnaround time and trip time. This has to be done while minimizing (costs of) deviations from desired times, platforms or lines, allowing for conflicts due to through-platforms, dead-end platforms, multiple sub-platforms, and possible constraints due to infrastructure, safety or business policy.

Is the General Public Licence a Rational Choice?

Open source projects are networks of developers, distributors and end-users of non-proprietary created knowledge goods. It has been argued that this form of organization has some advantages over the firm or market coordination. I show that for sufficiently convex and modular projects proprietary licences are not able to sustain sequential knowledge production which, however, can be carried out if the project is run on the open source basis.

Clinical implementation of dynamic multileaf collimation for compensated bladder treatments.

BACKGROUND AND PURPOSE: To describe the clinical implementation of dynamic multileaf collimation (DMLC). Custom compensated four-field treatments of carcinoma of the bladder have been used as a simple test site for the introduction of intensity modulated radiotherapy.MATERIALS AND METHODS: Compensating intensity modulations are calculated from computed tomography (CT) data, accounting for scattered, as well as primary radiation. Modulations are converted to multileaf collimator (MLC) leaf and jaw settings for dynamic delivery on a linear accelerator. A full dose calculation is carried out, accounting for dynamic leaf and jaw motion and transmission through these components. Before treatment, a test run of the delivery is performed and an absolute dose measurement made in a water or solid water phantom. Treatments are verified by in vivo diode measurements and real-time electronic portal imaging. RESULTS: Seven patients have been treated using DMLC. The technique improves dose homogeneity within the target volume, reducing high dose areas and compensating for loss of scatter at the beam edge. A typical total treatment time is 20 min. CONCLUSIONS: Compensated bladder treatments have proven an effective test site for DMLC in an extremely busy clinic.