A hybrid particle swarm for the distribution routing problem with simutaneous pickups and delivery service

In practical operations, exact methods was incapable of dealing with large scale logistics distribution routing problem variant which considers customers to simultaneously require delivery and pickups services (VRPSDP) instances within acceptable computational times. So the paper proposed mathematical formulations and designed an hybrid algorithm for VRPSDP. The algorithm incorporated the mutation and selection operation in particle swarm algorithm for logistics distribution routing problem variant. Using the selection and mutation which dynamic changed with the iterations could effectively prevent the algorithm into local optimum and converge to the global optimum ultimately. In specific, we introduced a self-adaptive parameter adjustment strategy in particle swarm algorithm, the proposed strategy could maximize the amount of routing information according to each iteration and drive the search towards diverse regions of the solution space. The performance of our hybrid algorithm was tested on some VRPSPD instances. It proved to be rather effective and efficient, as it produced high quality results, improving several best solutions previously reported.