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Journal of Transportation Engineering / Volume 136 / Issue 4 / TECHNICAL PAPERS / Transportation Systems

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Single-Stage Integer Programming Model for Long-Term Transit Fleet Resource Allocation

J. Transp. Eng. 136, 281 (2010); doi:10.1061/(ASCE)0733-947X(2010)136:4(281) (10 pages)

Sabyasachee Mishra1, Tom V. Mathew2, and Snehamay Khasnabis, M.ASCE3

1Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Wayne State Univ., 5050 Anthony Wayne Dr., Detroit, MI 48202. E-mail: hisabya@wayne.edu
2Associate Professor, Dept. of Civil Engineering, Transportation Systems Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400 076, India. E-mail: vmtom@civil.iitb.ac.in
3Professor, Dept. of Civil and Environmental Engineering, Wayne State Univ., 5050 Anthony Wayne Dr., Detroit, MI 48202. E-mail: skhas@eng.wayne.edu

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(Submitted 15 January 2008; accepted 20 November 2009; published online 15 March 2010)

The writers present a procedure for resource allocation among transit agencies for transit fleet management, specifically focusing on the purchase of new buses and rebuilding of existing buses. The model is formulated as a nonlinear optimization problem of maximizing the total weighted average remaining life of the fleet subject to budgetary, policy, and other constraints. The problem is solved using integer programming and its application is demonstrated through a case study using actual transit fleet data from the Michigan DOT. This proposed model is an extension of earlier research on a two-stage sequential optimization method, solved by linear programming. The proposed model has a single-stage structure designed to attain a better solution by allocating resources among different improvement options and different agencies in a single step. A comparison of the results by the two methods shows that while both approaches are viable, the single-stage approach produces better results. The proposed model, as demonstrated in the case study is considered more robust, compact, efficient and suitable for both short-term and long range planning.

© 2010 ASCE

Acknowledgments

The work on the topic was initiated by Khasnabis and his colleagues at Wayne State University (WSU) in 2002 through a research project supported by the federally funded University Transportation Center (UTC) program at the University of Wisconsin Madison that resulted in the development of the two-stage LP model. The single-stage model reported in this paper is an outgrowth of this earlier work, and represents a collaborative effort between WSU and the Indian Institute of Technology Bombay (IITB), India. The writers would like to express their sincere appreciation to: (1) U.S. DOT and the University of Wisconsin for the initial funding for the two-stage model; (2) the Fulbright Foundation and WSU for providing opportunities for research to Khasnabis on asset management with faculty members from IITB; and (3) the IITB for serving as the host institution for Khasnabis during his Fulbright research in India, thereby providing a forum for exchange of ideas with its students and faculty members. The support of MDOT for the PTMS database in the modeling exercises is thankfully acknowledged. The writers would like to acknowledge Transportation Research Board (TRB) for allowing the use of four tables of a previously published paper in this document (Khasnabis et al. 200417). Tables 1 , 2 , 3 , 4 of this paper are from “Transportation Research Record: Journal of the Transportation Research Board, No. 1887, Transportation Research Board of the National Academies, Washington, D.C., 2004. Table 1 p. 48; Table 2, p. 49; Table 3, p. 51; and Table 4, p. 52 are reproduced with permission of TRB. None of this material may be presented to imply endorsement by TRB of a product, method, practice, or policy. The opinions and viewpoints expressed in this paper are entirely those of the writers, and do not necessarily represent policies and programs of the aforementioned agencies.

Article Outline

  1. Introduction
  2. Literature Review
    1. REHAB and REMANF Issues
    2. Asset Management Issues
    3. Optimization Tools and Solution Approaches in Transit
  3. Model Development
    1. Two-Stage Model
    2. Single-Stage Model
    3. Formulation
  4. Case Study
    1. Two-Stage Model Results
    2. Single-Stage Model Results
    3. Synthesis of Two Approaches
  5. Conclusions

KEYWORDS

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http://dx.doi.org/10.1061/(ASCE)0733-947X(2010)136:4(281)

PUBLICATION DATA

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0733-947X (print)  
1943-5436 (online)

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ASCE

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