三维载荷约束下取货问题的改进混合启发式算法

Jiangqing Wu, Ling Zheng, Can Huang, Sifan Cai, Shaorong Feng, Defu Zhang
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引用次数: 5

摘要

在物流业中,车辆路线问题与集装箱装载问题的整合是一个非常具有挑战性的问题,它被概括为具有三维装载约束的取货和交货问题(3L-PDP)。这不仅包括确保最短的旅行路线,还包括尽量减少重新装货的工作量。对于这类复杂的问题,传统的优化方法如穷举搜索和贪婪搜索很难得到最优解。本文对3L-PDP问题的混合启发式算法进行了扩展,主要改进了两个方面:一是在模拟退火过程的框架下,使用禁忌策略来扩大大邻域搜索(LNS)算法的局部搜索空间;二是使用复杂块生成和深度优先启发式来在打包阶段逐步找到一个合适的盒子。实验结果表明,在Li和Lim或Dirk和Andreas提出的基准实例上,改进的混合启发式算法在总行程距离上优于原始算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Hybrid Heuristic Algorithm for Pickup and Delivery Problem with Three-Dimensional Loading Constraints
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.
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