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Algorithms for the Hybrid Fleet Vehicle Routing Problem

In the classical Vehicle Routing Problem (VRP) literature, as well as in most VRP commercial software packages, it is commonly assumed that all vehicles are identical in their characteristics. In real-world problems however, this is often not true. In many cases, fleets are made up of different vehicle types, which may vary by size, engine/fuel type, and other performance-impacting factors. Even in a homogeneous fleet, vehicles often differ by age and condition, which can greatly impact performance. Our research was specifically motivated by cases where the fleet contains vehicles that not only vary in performance, but this variation is a function of the arc type, such that a given vehicle might have lower cost on some arcs but higher cost on others. We refer to this as the Hybrid Fleet Vehicle Routing Problem (HFVRP). We propose two heuristic methods that take into account the vehicle-specific cost structures. We provide computational results to demonstrate the quality of our solutions, as well as a comparison with a Genetic Algorithm (GA) based method seen in the literature.