Formulations and Branch-and-Cut Algorithms for the Generalized Vehicle Routing Problem

The Generalized Vehicle Routing Problem (GVRP) consists of finding a set of routes for a number of vehicles with limited capacities on a graph with the vertices partitioned into clusters with given demands such that the total cost of travel is minimized and all demands are met. This paper offers four new integer linear programming formulations for the GVRP, two based on multicommodity flow and the other two based on exponential sets of inequalities. Branch-and-cut algorithms are proposed for the latter two. Computational results on a large set of instances are presented.