This paper shows how idealized models can be used to obtain cost-effective, implementable solutions to large and complex logistics problems. It advocates the use of fine tuning software to translate the guidelines produced by idealized models into specific feasible solutions. The “traveling salesman” (TSP) and “vehicle routing” (VRP) problems were used to test the approach. For sufficiently large problems the proposed procedure leads to solutions that improve on those produced by either idealized models or numerical methods alone. Simulated annealing (SA) was chosen for fine tuning. This optimization procedure is ideally suited for this purpose because of its general applicability, and as the research demonstrates, a prototype software package can be quickly produced. The experiments also revealed that the TSP and VRP tour lengths predicted by the idealized models are close (surprisingly so in some cases) to those of actual tours.