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

Authors:
Verena Schmid;Karl F. Doerner;Richard F. Hartl;Juan-José Salazar-González
Affiliations:
Department of Business Administration, University of Vienna, Bruenner Strasse 72, 1210 Vienna, Austria;Department of Business Administration, University of Vienna, Bruenner Strasse 72, 1210 Vienna, Austria;Department of Business Administration, University of Vienna, Bruenner Strasse 72, 1210 Vienna, Austria;Facultad de Matemáticas, Universidad de La Laguna, 38271 La Laguna, Tenerife, Spain
Venue:
Computers and Operations Research
Year:
2010

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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.