A Hybrid Branch-and-Cut Approach for the Capacitated Vehicle Routing Problem

This paper presents a hybrid optimization approach that combines deterministic and metaheuristic algorithms for the Capacitated Vehicle Routing Problem (CVRP). The approach combines a new branch-and-cut framework, that utilizes a two-commodity flow representation and novel heuristic-based procedures to separate various classes of cuts, with a subordinate Adaptive Memory Programming metaheuristic algorithm for the identification of high quality solutions. New local-scope cuts are suggested to exclude infeasible or suboptimal solutions, break problem symmetries, and tighten constraints. Computational experiments illustrate the potential of the new approach.