Preserving an aging transit fleet: An optimal resource allocation perspective based on service life and constrained budget

• Published in: Transportation research. Part A, Policy and practice Policy and practice, 2013-01, Vol.47, p.111-123
• Main Authors: Mishra, Sabyasachee, Sharma, Sushant, Khasnabis, Snehamay, Mathew, Tom V.
• Format: Article
• Language: English
• Subjects: Applied sciences; Branch and bound algorithm; Exact sciences and technology; Ground, air and sea transportation, marine construction; Integer programming; Net present cost; Road transportation and traffic; Transit fleet; Transportation planning, management and economics
• ISSN: 0965-8564; 1879-2375
• DOI: 10.1016/j.tra.2012.10.029

► NPC can serve as a potential indicator in fleet management. ► NPC is affected by the time of the investment within the planning period. ► The relationship between NPC and TSWARL is non-linear. ► Minimum NPC value can serve to assist in fleet rebuilding decision making. Local, county and state level transit agencies with large fleets of buses and limited budgets seek a robust fund allocation mechanism to maintain service standards. However, equitable and optimal fund allocation for purchasing, operating and maintaining a transit fleet is a complex process. In this study, we develop an optimization model for allocation of funds among different fleet improvement programs within budget constraints over the planning period. This is achieved by minimizing the net present cost (NPC) of the investment within the constraint of a minimum level of fleet quality expressed as a surrogate of the remaining life of the fleet. Integer programming is used to solve the formulated optimization problem using branch and bound algorithm. The model formulation and application are demonstrated with a real world case study of transit agencies. It is observed that minimizing NPC provides a realistic way to allocate resources between different program options among different transit agencies while maintaining a desired quality level. The proposed model is generalized and can be used as a resource allocation tool for transit fleet management by any transit agency.