Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Computers and Operations Research
Network Models in Optimization and Their Applications in Practice
Network Models in Optimization and Their Applications in Practice
A Reactive Variable Neighborhood Search for the Vehicle-Routing Problem with Time Windows
INFORMS Journal on Computing
An efficient variable neighborhood search heuristic for very large scale vehicle routing problems
Computers and Operations Research
Hybridization of very large neighborhood search for ready-mixed concrete delivery problems
Computers and Operations Research
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
Hybridization of very large neighborhood search for ready-mixed concrete delivery problems
Computers and Operations Research
HM '09 Proceedings of the 6th International Workshop on Hybrid Metaheuristics
Combining Exact and Heuristic Approaches for the Capacitated Fixed-Charge Network Flow Problem
INFORMS Journal on Computing
Survey: matheuristics for rich vehicle routing problems
HM'10 Proceedings of the 7th international conference on Hybrid metaheuristics
A branch-and-price guided search approach to maritime inventory routing
Computers and Operations Research
Improved Load Plan Design Through Integer Programming Based Local Search
Transportation Science
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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.