| The passage of the Motor Carrier Act of 1980 diversified distribution managers' transportation strategies. The diverse transportation options provide the significant opportunity for substantial transportation cost savings, which have encouraged many companies to reassess the design of their current transportation systems. The most "productive" transportation options include consolidating small shipments across different products/routes which originate from multiple depots and capitalizing on backhauls by the use of private carriers.;After transportation deregulation, the existing vehicle routing models which did not take into account these real variations were no longer viable for private fleets. In this research, improved vehicle routing models are proposed which incorporate the aforementioned deregulatory options into the mathematical modeling process. In addition, to efficiently solve the vehicle routing problem utilizing product/spatial consolidation and backhauling (VRPCB), this study decomposes the VRPCB into three subproblems: allocation of customers and vendors to depots, determination of fleet size, and routing of vehicles.;This decomposition process is supported by three different solution techniques which complement each other. These include (1) "capacitated" clustering analysis, (2) a linear programming relaxation method, and (3) an "aggregate" and "disaggregate" tour-building procedure. Computational experience with each of these for large-sized problems is reported. Computational results show that the proposed solution techniques are capable of handling the practical size problem with 398 customers, 58 vendors, 10 depots and 45 vehicles. Even larger-sized VRPCB's can be solved with minor modifications of the decomposition procedure.;Finally, in an effort to demonstrate the practicality of the proposed models and solution techniques, applications of these to a real-world problem setting based on actual data are presented. The potential for dealing with various scenarios of VRPCB's is also demonstrated. |
