Abstract Travel scheme planning is a crucial operational-level decision to be made in travel supply chain management. We investigate an integrated self-driving travel scheme planning (ISTSP) problem to optimize routing, hotel selection, and time scheduling under several streams of personalized considerations: best site-viewing time windows, rest requirements, and preference for site visiting sequences. The travel scheme planning problem is formulated in two models: (i) total cost minimization, and (ii) bi-objective optimization with total cost minimization and tourists’ utility maximization. A heuristic solution framework integrating multi-categorical attribute K-means clustering, dynamic programming algorithm, and constraint satisfaction procedure is designed to solve these two models. Finally, we provide illustrative examples to demonstrate the effectiveness and validity of the proposed models and solution methods.

中文翻译：

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一体化自驾出行方案规划

摘要 旅游计划规划是旅游供应链管理中一个关键的运营层面决策。我们研究了一个集成的自动驾驶旅行计划规划 (ISTSP) 问题，以在多种个性化考虑因素下优化路线、酒店选择和时间安排：最佳站点查看时间窗口、休息要求和站点访问顺序的偏好。旅行计划规划问题用两种模型表示：(i) 总成本最小化，和 (ii) 总成本最小化和游客效用最大化的双目标优化。结合多分类属性K-means聚类、动态规划算法和约束满足程序的启发式求解框架被设计来求解这两个模型。最后，