An ILS-biased randomization algorithm for the two-dimensional loading HFVRP with sequential loading and items rotation
针对现实中常见的异构车队、二维装载、顺序装载和物品旋转约束的车辆路径问题，提出一种集成偏随机化启发式的迭代局部搜索算法，能在较短计算时间内获得高质量解。
This paper discusses the Two-dimensional Loading Vehicle Routing Problem with Heterogeneous Fleet, Sequential Loading, and Item Rotation (2L-HFVRP-SR). Despite the fact that the 2L-HFVRP-SR can be found in many real-life situations related to the transportation of voluminous items, where heterogeneity of fleets, two-dimensional packing restrictions, sequential loading, and items rotation have to be considered, this rich version of vehicle routing-and-packing problem has been rarely analysed in the literature. Accordingly, this paper contributes to filling the gap by presenting a relatively simple-to-implement algorithm which is able to provide state-of-the-art solutions for such a complex problem in relatively short computational times. The proposed algorithm integrates inside an Iterated Local Search framework, biased-randomized versions of both vehicle routing and packing heuristics. The efficiency of the proposed algorithm is validated throughout an extensive set of computational tests.