The delivery man problem and cumulative matroids
Operations Research
A genetic algorithm for the vehicle routing problem with time-dependent travel times
A genetic algorithm for the vehicle routing problem with time-dependent travel times
A Two-Phase Genetic and Set Partitioning Approach for the Vehicle Routing Problem with Time Windows
HIS '04 Proceedings of the Fourth International Conference on Hybrid Intelligent Systems
Solving the Vehicle Routing Problem with Stochastic Demands and Customers
PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
A Hybrid Approach for the Dynamic Vehicle Routing Problem with Time Windows
HIS '05 Proceedings of the Fifth International Conference on Hybrid Intelligent Systems
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
Optimal vehicle routing with real-time traffic information
IEEE Transactions on Intelligent Transportation Systems
A satellite navigation system to improve the management of intermodal drayage
Advanced Engineering Informatics
Multi-environmental cooperative parallel metaheuristics for solving dynamic optimization problems
The Journal of Supercomputing
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The dynamic vehicle routing problem is one of the most challenging combinatorial optimization tasks. The interest in this problem is motivated by its practical relevance as well as by its considerable difficulty. We present an approach to search for best routes in dynamic network. We propose a dynamic route evaluation model for modeling the responses of vehicles to changing traffic information, a modified Dijkstra's double bucket algorithm for finding the real-time shortest paths, and an improved evolutionary algorithm for searching the best vehicle routes in dynamic network. The proposed approach has been evaluated by simulation experiment using DVRPSIM. It has been found that the proposed approach quite efficient in finding real-time best vehicle routes where the customer nodes and network information changes dynamically.