Multiobjective Optimization Model for Transit Fleet Resource Allocation

State and local transit agencies require government support to preserve their aging transit fleets. With the passage of time, transit fleets get older and require maintenance costs to keep them operational. To provide services at a desired level, transit agencies must maintain a minimum fleet size. Two imperative considerations from the transit planning viewpoint are (a) the remaining life of the total fleet and (b) the cost required to maintain the fleet size. While the former is a quality measure indicating the health of the fleet, the latter is an economic measure requiring minimum expenditure levels. Ideally, agencies would like to maximize the total remaining life of the fleet and minimize the total cost required to maintain the fleet size. In this paper, a multiobjective optimization (MO) model is proposed to incorporate simultaneously the two objectives when subjected to budget and various operational constraints. The MO problem is solved with a classical weight sum approach by using the branch and bound algorithm, which has proved to be better than other solution methodologies. The MO results in Pareto-optimal solutions with possible trade-offs between the two objectives. The model is applied to a large-scale transit fleet system in the state of Michigan. The case study results demonstrate that the proposed model is compact, efficient, robust, and suitable for long-range planning with multiple solutions to choose from a Pareto-optimal frontier. The correlation between decision variables and objective functions has been investigated in-depth, providing important insights. The proposed model can act as a tool for resource allocation for state and local agency transit fleets.

[1]  James F. Foerster.  Bus Maintenance Cost Control , 1985 .

[2]  James E. Falk,et al.  Optimal deviations from an asset allocation , 2003, Comput. Oper. Res..

[3]  Anthony D. Ross,et al.  Performance-based strategic resource allocation in supply networks , 2000 .

[4]  Antonella Basso,et al.  Optimal resource allocation with minimum activation levels and fixed costs , 2001, Eur. J. Oper. Res..

[5]  Richard S. Marshment.  ESTABLISHING NATIONAL PRIORITIES FOR RAIL TRANSIT INVESTMENTS , 1993 .

[6]  Amelia C. Regan,et al.  Network-based real option models , 2011 .

[7]  Thomas H Maze,et al.  THEORY AND PRACTICE OF TRANSIT BUS MAINTENANCE PERFORMANCE MEASUREMENT , 1987 .

[8]  John Collura,et al.  Developing a Decision Support System for Evaluating an Investment in Fare Collection Systems in Transit , 2003 .

[9]  Snehamay Khasnabis,et al.  Preserving an aging transit fleet: An optimal resource allocation perspective based on service life and constrained budget , 2013 .

[10]  Wei Gao,et al.  Optimization Method for Train Plan of Urban Rail Transit , 2011 .

[11]  Frank DiCesare,et al.  TRANSIT SERVICE EVALUATION: PRELIMINARY IDENTIFICATION OF VARIABLES CHARACTERIZING LEVEL OF SERVICE , 1976 .

[12]  Lester A Hoel,et al.  APPLICATION OF A TRANSIT MAINTENANCE MANAGEMENT EVALUATION PROCEDURE , 1986 .

[13]  Thomas H Maze,et al.  Model for Comparing Performance of Various Transit Maintenance Repair Policies , 1989 .

[14]  M S Bridgman,et al.  ECONOMIC COMPARISON OF NEW BUSES VERSUS REHABILITATED BUSES , 1983 .

[15]  M. Karlaftis,et al.  Fund Allocation for Transportation Network Recovery Following Natural Disasters , 2007 .

[16]  Douglas W Carter,et al.  EVALUATION OF BUS MAINTENANCE MANPOWER UTILIZATION , 1985 .

[17]  Snehamay Khasnabis,et al.  Optimal resource allocation among transit agencies for fleet management , 2010 .

[18]  Snehamay Khasnabis,et al.  Single-Stage Integer Programming Model for Long-Term Transit Fleet Resource Allocation , 2010 .

[19]  Jannes Slomp,et al.  An integrated model for part-operation allocation and investments in CNC technology , 2002 .

[20]  Chris Hendrickson,et al.  Innovative Strategies to Improve Urban Transportation Performance , 1985 .

[21]  Lazar N Spasovic,et al.  BUS TRANSIT SERVICE COVERAGE FOR MAXIMUM PROFIT AND SOCIAL WELFARE , 1994 .

[22]  Jiuh-Biing Sheu,et al.  A novel dynamic resource allocation model for demand-responsive city logistics distribution operations , 2006 .

[23]  Xuehao Chu,et al.  Considering Build-Later as an Alternative in Major Transit Investment Analyses , 1998 .

[24]  B B Balzer,et al.  SURVEY AND ANALYSIS OF BUS REHABILITATION IN THE MASS TRANSPORTATION INDUSTRY , 1980 .

[25]  Albert Gan,et al.  Multiobjective Optimization Model for Prioritizing Transit Stops for ADA Improvements , 2011 .

[26]  M S Bridgman,et al.  FEASIBILITY OF DETERMINING ECONOMIC DIFFERENCES BETWEEN NEW BUSES AND REHAB BUSES , 1984 .

[27]  Michail Litvinenko,et al.  THE EVALUATION OF TRANSIT TRANSPORT PROBABLE EFFECTS ON THE DEVELOPMENT OF COUNTRY'S ECONOMY , 2006 .

[28]  Antonio Mauttone,et al.  A multi-objective metaheuristic approach for the Transit Network Design Problem , 2009, Public Transp..

[29]  C Giuliani.  BUS INSPECTION GUIDELINES , 1987 .

[30]  Sushant Sharma,et al.  Multiobjective Network Design for Emission and Travel-Time Trade-off for a Sustainable Large Urban Transportation Network , 2011 .

[31]  Lester A Hoel,et al.  EVALUATION OF BUS MAINTENANCE OPERATIONS , 1985 .

[32]  Sheldon S. Williamson,et al.  Optimal drivetrain component sizing for a Plug-in Hybrid Electric transit bus using Multi-Objective Genetic Algorithm , 2010, 2010 IEEE Electrical Power & Energy Conference.

[33]  S. Raju,et al.  Project NPV, Positive Externalities, Social Cost-Benefit Analysis-The Kansas City Light Rail Project , 2008 .