Open AccessOptimization Model for Rail Line Crossover Design Considering the Cost of Delay
Author(s) -
W.W.T. Trommelen,
Konstantinos Gkiotsalitis,
Eric C. van Berkum
Publication year - 2021
Publication title -
transportation research record
Language(s) - English
Resource type - Journals
eISSN - 2169-4052
pISSN - 0361-1981
DOI - 10.1177/03611981211062488
Subject(s) - crossover , set (abstract data type) , selection (genetic algorithm) , relation (database) , line (geometry) , operations research , choice set , genetic algorithm , reduction (mathematics) , computer science , mathematical optimization , engineering , reliability engineering , econometrics , mathematics , data mining , geometry , artificial intelligence , programming language
In this study, we introduce a method to optimally select the crossover locations of an independent rail line from a set of possible crossover locations considering a fixed number of crossovers that must be used in the design. This optimal selection aims to minimize the cost of passenger delay. Previous research showed that including passenger delay in the decision of rail design choices could be beneficial from economic and societal perspectives. However, those studies were only able to evaluate a few alternatives, because the degraded schedules had to be determined manually. In this research, we introduced an integer nonlinear model to find the best crossover design. We further developed an algorithm to evaluate a set of crossovers and determine the cost of delays for all segments on a rail line given a set of potential disruptions. The monetized cost of passenger delays was used to analyze the tradeoff between the unreliability costs emerging from the delay of passengers in the case of disruptions, and the total number of required crossovers. Our model was applied on a light rail line in Bergen (Norway) resulting in 10% reduction in relation to passenger delays without increasing the number of crossovers; thus, ensuring that there were no additional costs.