A GENETIC ALGORITHM APPROACH FOR SOLVING THE TRAIN FORMATION PROBLEM

The train formation plan is one of the most important elements of railroad system operations. Although mathematical programming formulations and algorithms are available for solving the train formation problem (TFP), the computational time required for their convergence is usually excessive. At the same time, shorter decision intervals are becoming necessary given the highly competitive operating climates of the railroad industry. Thus, new techniques are needed for generating efficient solutions for the TFP. In this study, the authors present the development of a genetic algorithm (GA) as a possible technique for this problem. The calibration and validation of the GA model are carried out for three different complexity levels of objective functions. It is found that the optimal solutions can be found for all the different formulations while consuming only a small amount of computation time.

• Record URL:
  • http://onlinepubs.trb.org/Onlinepubs/trr/1995/1497/1497-008.pdf
• Record URL:
  • https://scholar.google.com/scholar_lookup?title=A+GENETIC+ALGORITHM+APPROACH+FOR+SOLVING+THE+TRAIN+FORMATION+PROBLEM&author=D.+Martinelli&author=H.+Teng&publication_year=1995
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• Supplemental Notes:
  • This paper appears in Transportation Research Record No. 1497, Artificial Intelligence and Geographical Information. Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved
• Authors:
  • Martinelli, David
  • Teng, Hualiang
• Publication Date: 1995

Language

• English

Media Info

• Features: Figures; References; Tables;
• Pagination: p. 62-69
• Monograph Title: Artificial intelligence and geographical information
• Serial:
  • Transportation Research Record
  • Issue Number: 1497
  • Publisher: Transportation Research Board
  • ISSN: 0361-1981

Subject/Index Terms

• TRT Terms: Calibration; Genetic algorithms; Train makeup; Validation
• Uncontrolled Terms: Computation time
• Old TRIS Terms: Train formation problem
• Subject Areas: Freight Transportation; Highways; Planning and Forecasting; Railroads;

Filing Info

• Accession Number: 00714944
• Record Type: Publication
• ISBN: 0309061636
• Files: TRIS, TRB
• Created Date: Dec 20 1995 12:00AM