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

Abstract

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 two hybrid solution procedures for dealing with this problem. They are based on a combination of an exact algorithm and a variable neighborhood search (VNS) approach. 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 approaches follows a local branching scheme. The hybrid metaheuristics are compared with the pure VNS approach and the conclusion is that the new metaheuristics outperform the VNS if applied solely.