Technological innovation has been reshaping all walks of life, and the marine shipping industry is no exception. Autonomous vessels have gained significant attention due to their numerous advantages. However, regulatory constraints and expensive manufacturing costs are impeding the application of autonomous vessels. To overcome these challenges, this research conducts experiments with autonomous ships on national waterways with less regulation and develops a model to investigate their impact on shipping company operations. The model simultaneously optimizes ship routing, fleet sizing, fleet deployment, and demand fulfillment, taking into account demand uncertainty. Two solution methods, i.e., sample average approximation and a two-phase Benders-based branch-and-cut algorithm, are proposed to solve the problem with acceleration strategies, including column generation and variable fixing. The performance of several solution techniques is tested through numerical experiments using real-world data. Besides, sensitivity analyses are conducted to further discuss the influence of key factors and derive constructive managerial insights for shipping companies.

科技创新正在重塑各行各业，海运业也不例外。自主船舶因其众多优势而受到广泛关注。然而，监管限制和昂贵的制造成本阻碍了自主船舶的应用。为了克服这些挑战，本研究在监管较少的国家水道上对自主船舶进行了实验，并开发了一个模型来调查其对航运公司运营的影响。该模型同时优化船舶航线、船队规模、船队部署和需求满足，同时考虑到需求的不确定性。提出了两种求解方法，即样本平均近似和基于Benders的两阶段分支剪切算法，以加速策略（包括列生成和变量固定）求解问题。通过使用真实世界数据的数值实验来测试几种求解技术的性能。此外，还进行敏感性分析，进一步探讨关键因素的影响，为航运企业提供建设性的管理见解。