Asset Management of Vehicles: A Practical Application of the Logic Scoring of Preference Method of Optimizing Programmatic Investment Decisions in a Performance based System

摘要

This paper is an application of the Logic Scoring of Preference (LSP) methodology, a second-order decision model, to asset management of a public agency vehicle fleet. Current vehicle allocation management (VAM) modeling can readily identify the best and worst vehicles of the fleet, but does not adequately address the remaining vehicles in the fleet. Five weighted preferences are applied to assessment of mission role, age, fuel type, miles per gallon and cumulative mileage. These weighted preferences are then further optimized, providing a measure of how well the model is close to an ideal solution (benefits). A life- cycle cost is then generated for each vehicle. These two inputs create a benefit-cost ratio for each vehicle which will allow for a unique side-by-side comparison of all vehicles in the fleet, a much needed improvement over current VAM modeling.