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

Abstract

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.