Artificial intelligence (AI) applications are the core challenge for engineering and management science concepts in production and logistics within the next decade. This study analyses the application of AI instances in route planning as a central part of logistics management from an empirical case perspective for retail logistics in Germany. The methods applied encompass fuzzy data envelopment analysis (DEA), slack-based measurement (SBM) fuzzy DEA, and analytic hierarchy process (AHP)-SBM Fuzzy DEA. For the two depots using AI-based routing to the full account, efficiency advantages can be shown in the Fuzzy DEA as well as the SBM fuzzy DEA models. Results further indicate that the methodological approach is adequate for the analysed problem and that the combination with AHP is an interesting addition as, e.g., the perspective of sales managers supersedes that of logistics managers for route planning efficiency – a thought-provoking result pointing at very customer-oriented logistics systems.

人工智能 (AI) 应用是未来十年内生产和物流领域工程和管理科学概念的核心挑战。本研究从德国零售物流的实证案例角度分析了人工智能实例在路线规划中作为物流管理核心部分的应用。应用的方法包括模糊数据包络分析 (DEA)、基于松弛的测量 (SBM) 模糊 DEA 和层次分析法 (AHP)-SBM 模糊 DEA。对于使用基于 AI 的路由到全账户的两个站点，在模糊 DEA 和 SBM 模糊 DEA 模型中都可以显示效率优势。结果进一步表明，该方法论方法足以解决所分析的问题，并且与 AHP 的结合是一个有趣的补充，例如，