Hybridization of very large neighborhood search for ready-mixed concrete delivery problems

Companies in the concrete industry are facing the following scheduling problem on a daily basis: concrete produced at several plants has to be delivered at customers’ construction sites using a heterogeneous fleet of vehicles in a timely, but cost-effective manner. The distribution of ready-mixed concrete (RMC) is a highly complex problem in logistics and combinatorial optimization. This paper proposes a hybrid solution procedure for dealing with this problem. It is based on a combination of an exact algorithm and a Variable Neighborhood Search approach (VNS). The VNS is used at first to generate feasible solutions and is trying to further improve them. The exact method is based on a Mixed Integer Linear Programming (MILP) formulation, which is solved (after an appropriated variable fixing phase) by using a general-purpose MILP solver. An approach based on Very Large Neighborhood Search (VLNS) determines which variables are supposed to be fixed. In a sense, the approach follows a local branching scheme. The hybrid metaheuristic is compared with the pure VNS approach and the conclusion is that the new metaheuristic outperforms the VNS if applied