Christos D. Zaroliagis – författare

This work considers practical parallel list-ranking algorithms. The model for which programs are written is a single-program multiple-data (SPMD) \bri- ingmodel". Thismodel isdesignated asa programmer'smodelfora ne-grained computation framework called Explicit Multi-Threading (XMT), which was - troduced in [VDBN98]; the XMT framework covers the spectrum from al- rithms through architecture to implementation; it is meant to provide a pl- form for faster single-task completion time by way of instruction-level par- lelism (ILP). The performance of XMT programs is evaluated as follow: the performance of a matching optimized XMT assembly code is measured within an XMT execution model. (We use in the current paper the so-called Spawn- MT programmingmodel - the easier to implement amongthe two programming modelspresented in[VDBN98]). The XMT approach deviatesfromthe standard PRAM approach by incorporating reduced synchrony and departing from the lock-step structure in its so-called asynchronous mode. Our envisioned platform uses an extension to a standard serial instruction set.This extension e ciently implements PRAM-style algorithms using explicit multi-threaded ILP, which allows considerably more n e-grained parallelism than the previously studied parallel computing implementation platforms/models. The list ranking problem was the rst problem considered as we examined and re ned many of the concepts in the XMT framework. The problem arises in parallel algorithmson lists, trees and graphs and is considered a fundamental problemin the theory of parallelalgorithms. Experimental results are presented.

Scheduled transportation networks give rise to very complex and large-scale networkoptimization problems requiring innovative solution techniques and ideas from mathematical optimization and theoretical computer science. Examples of scheduled transportation include bus, ferry, airline, and railway networks, with the latter being a prime application domain that provides a fair amount of the most complex and largest instances of such optimization problems. Scheduled transport optimization deals with planning and scheduling problems over several time horizons, and substantial progress has been made for strategic planning and scheduling problems in all transportation domains.This state-of-the-art survey presents the outcome of an open call for contributions asking for either research papers or state-of-the-art survey articles. We received 24 submissions that underwent two rounds of the standard peer-review process, out of which 18 were finally accepted for publication.The volume is organized in four parts: Robustness and Recoverability, Robust Timetabling and Route Planning, Robust Planning Under Scarce Resources, and Online Planning: Delay and Disruption Management.