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. As the ordered quantity of concrete typically exceeds the capacity of a single vehicle several deliveries need to be scheduled in order to fulfill an order. The deliveries cannot overlap and the time between consecutive deliveries has to be small. Our solution approach effectively integrates optimization and heuristic techniques. Information is passed back and forth between an integer multicommodity flow optimization component and a variable neighborhood search component in order to find high-quality solutions in a reasonable amount of time. Even though both components are capable of producing feasible solutions, the integrated approach is far more effective. Computational results show that our hybrid approach outperforms an innovative metaheuristic approach by more than 6% on average for large instances.

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