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Optimizing dispatching of public transit vehicles using genetic simulated annealing algorithm

  • Chuan Xiang Ren*
  • , Hai Zhang
  • , Yue Zu Fan
  • *Corresponding author for this work
  • Beihang University

Research output: Contribution to journalArticlepeer-review

Abstract

Public transit vehicle dispatching is the main task of the agency, which affects the agency's economic and social benefits. The vehicle scheduling model was set up with giving attention to the benefits to the agency and passengers. Genetic Algorithm and Simulated Annealing Algorithm were combined to become Hybrid Genetic Algorithms, namely GA-SA, and then the public vehicle scheduling was optimized. The results of the simulation indicate GA-SA has the higher efficiency than simple GA and is one effective way optimizing the public transit vehicle dispatching.

Original languageEnglish
Pages (from-to)2075-2077+2081
JournalXitong Fangzhen Xuebao / Journal of System Simulation
Volume17
Issue number9
StatePublished - Sep 2005

Keywords

  • Genetic algorithms
  • Hybrid genetic algorithms
  • Public transport
  • Simulated annealing

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