An Improved Hybrid Heuristic Algorithm for Pickup and Delivery Problem with Three-Dimensional Loading Constraints

Jiangqing Wu, Ling Zheng, Can Huang, Sifan Cai, Shaorong Feng, Defu Zhang

Abstract: In the logistics industry, the integration of the vehicle routing problem and the container loading problem which has been generalised as pickup and delivery problem with three-dimensional loading constraints (3L-PDP) is very challenging. It involves not only ensuring the shortest route of travel but also minimising the effort of reloading goods. Traditional optimisation methods such as exhaustive search and greedy search are hard to achieve an optimal solution for such kinds of complex problems. In this paper, a hybrid heuristic algorithm for the 3L-PDP problem is extended by two key improvements: the usage of a tabu strategy for enlarging the local search space of the large neighbourhood search (LNS) algorithm, which is proposed in the framework of the simulated annealing process, and the employment of complex block generation and depth-first heuristic for incrementally finding one proper box at a time in the packing phase. The experimental results show that the improved hybrid heuristic algorithm outperforms its origin regarding total travel distance on benchmark instances proposed by Li and Lim or Dirk and Andreas.