Finding robust periodic timetables by integrating delay management

This paper defines and solves a mathematical model for finding robust periodic timetables by proposing an extension of the Periodic Event Scheduling Problem (PESP). In order to model delayed and non-nominal travel times already in the timetabling step, the aim of this paper is to integrate delay management into the periodic timetabling problem and investigating the resulting problem (RPT). After revisiting both (PESP) and delay management individually, we introduce a periodic delay management model – an auxiliary model capable of evaluating periodic timetables with respect to delay resistance. Having introduced periodic delay management, we define the robust periodic timetabling problem (RPT). Due to the high complexity of the robust periodic timetabling problem we propose two different simplifications of the problem and introduce solution algorithms for both of them. These solution algorithms are tested against timetables found by standard procedures for periodic timetabling with respect to their delay-resistance. The computational results show that our algorithms yield timetables which can cope better with occurring delays, even on large-scale datasets and with low computational effort

Documentation for LinTim 2020.02

LinTim is a scientific software toolbox that has been under development since 2007, giving the possibility to solve the various planning steps in public transportation. Although the name originally derives from "Lineplanning and Timetabling", the available functions have grown far beyond this scope. This document is the documentation for version 2020.02. For more information, see https://www.lintim.ne

Documentation for LinTim 2020.02

LinTim is a scientific software toolbox that has been under development since 2007, giving the possibility to solve the various planning steps in public transportation. Although the name originally derives from "Lineplanning and Timetabling", the available functions have grown far beyond this scope. This document is the documentation for version 2020.02. For more information, see https://www.lintim.ne

A Bioinformatics Pipeline for the Detection of β-lactamase Genes in Metagenome Sequence Data and its Application to Production-Scale Biogas Plants

Osterholz B, Wiebke P, Fust A, Rumming M, Schlüter A, Sczyrba A. A Bioinformatics Pipeline for the Detection of β-lactamase Genes in Metagenome Sequence Data and its Application to Production-Scale Biogas Plants. Presented at the 3rd International Symposium on the environmental Dimension of Antibiotic Resistance, Wernigerode