Abstract: To advance scale merit of the logistics network, and balance the conflicts of interests between operators and customers, an optimization strategy of task-route matching is proposed on the basis of multi-hub and spoke collaborative logistics network.Firstly, under the condition of a given logistics network, considering resource departure time, capability limitation, dynamic cost discount coefficient and task delay penalty, a mathematical model oftask-route matching is established, which is from the point of logistics integration service provider and committed tominimize total cost as well as total time. Then,according to the characteristics of the problem, the genetic algorithm based on three-layers code is designed to solve the model. Meanwhile,the multi-point crossover and mutation mechanism are used to improve computing efficiency.Finally, research results show that centralized transportation could significantly reduce the execution cost of the task set,however, when the negative effect such as delivery delay and customer satisfaction decrease have exceeded the positive effect it brought about, the direct transport route should be appropriately introduced to improve the overall benefit.

Key words: hub and spoke network, collaborative logistics, logistics integration service provider, optimization of task-route matching, genetic algorithm