Abstract
AbstractThe Vehicle Routing Problem with Time Windows relates to frequently occuring real world problems in logistics. Much work has been done on solving static routing problems but solving the dynamic variants has not been given an equal amount of attention, while these are even more relevant to most companies in logistics and transportation. In this work an Ant Colony Optimization algorithm for solving the Dynamic Vehicle Routing Problem with Time Windows is proposed. Customers and time windows are inserted during the working day and need to be integrated in partially committed solutions. Results are presented on a benchmark that generalizes Solomon’s classical benchmark with varying degrees of dynamicity and different variants, including pheromone preservation and the min-max ant system.KeywordsTime WindowVehicle Route ProblemVehicle Route Problem With Time WindowCapacitate Vehicle Route ProblemTravel Salesperson ProblemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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