Use of a genetic algorithm to improve the rail profile on Stockholm underground

Ingemar Persson, Rickard Nilsson, Ulf Bik, Magnus Lundgren, Simon Iwnicki

Research output: Contribution to journalArticlepeer-review

46 Citations (Scopus)


In this paper, a genetic algorithm optimisation method has been used to develop an improved rail profile for Stockholm underground. An inverted penalty index based on a number of key performance parameters was generated as a fitness function and vehicle dynamics simulations were carried out with the multibody simulation package Gensys. The effectiveness of each profile produced by the genetic algorithm was assessed using the roulette wheel method. The method has been applied to the rail profile on the Stockholm underground, where problems with rolling contact fatigue on wheels and rails are currently managed by grinding. From a starting point of the original BV50 and the UIC60 rail profiles, an optimised rail profile with some shoulder relief has been produced. The optimised profile seems similar to measured rail profiles on the Stockholm underground network and although initial grinding is required, maintenance of the profile will probably not require further grinding.

Original languageEnglish
Pages (from-to)89-104
Number of pages16
JournalVehicle System Dynamics
Issue numberSUPPL. 1
Publication statusPublished - 2010
Externally publishedYes


Dive into the research topics of 'Use of a genetic algorithm to improve the rail profile on Stockholm underground'. Together they form a unique fingerprint.

Cite this