With the advent of e-commerce and its fast-delivery expectations, efficiently routing pickers in warehouses and distribution centers has received renewed interest. The processes and the resulting routing problems in this environment are diverse. For instance, not only human pickers have to be routed but also autonomous picking robots or mobile robots that accompany human pickers. Traditional picker routing, in which a single picker has to visit a given set of picking positions in a picker-to-parts process, can be modeled as the classical Traveling Salesman Problem (TSP). The more involved processes of e-commerce fulfillment, however, require solving more complex TSP variants, such as the clustered, generalized, or prize-collecting TSP. In this context, our paper provides two main contributions: We systematically survey the large number of TSP variants that are known in the routing literature and check whether meaningful applications in warehouses exist that correspond to the respective TSP variant. If they do, we survey the existing research and investigate the computational complexity of the TSP variant in the warehousing context. Previous research has shown that the classical TSP is efficiently solvable in the parallel-aisle structure of warehouses. Consequently, some TSP variants also turn out to be efficiently solvable in the warehousing context, whereas others remain -hard. We survey existing complexity results, provide new ones, and identify future research needs.

中文翻译：

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关于旅行商问题及其在仓储环境中的变体的调查

随着电子商务的出现及其对快速交货的期望，仓库和配送中心的高效路由拣选员重新引起了人们的兴趣。此环境中的过程和由此产生的路由问题是多种多样的。例如，不仅需要对人类拣选员进行路线安排，还需要对自动拣选机器人或伴随人类拣选员的移动机器人进行路线安排。传统的拣选路线，其中单个拣选人员必须在拣选到零件的流程中访问一组给定的拣选位置，可以将其建模为经典的旅行商问题 (TSP)。然而，电子商务履行过程越复杂，就越需要解决更复杂的 TSP 变体，例如集群式、通用式或有奖收集式 TSP。在这种情况下，我们的论文提供了两个主要贡献：我们系统地调查了路由文献中已知的大量 TSP 变体，并检查仓库中是否存在与相应 TSP 变体相对应的有意义的应用程序。如果确实如此，我们会调查现有研究并研究仓储环境中 TSP 变体的计算复杂性。先前的研究表明，经典的 TSP 在仓库的平行通道结构中可以有效解决。因此，一些 TSP 变体在仓储环境中也被证明可以有效解决，而其他变体仍然很难解决。我们调查现有的复杂性结果，提供新的结果，并确定未来的研究需求。