We combine ideas from uni-directional and bi-directional heuristic search, and approximation algorithms for the Traveling Salesman Problem, to develop a novel framework for a Multi-Goal Path Finding (MGPF) problem that provides a 2-approximation guarantee. MGPF aims to find a least-cost path from an origin to a destination such that each node in a given set of goals is visited at least once along the path. We present numerical results to illustrate the advantages of our framework over conventional alternates in terms of the number of expanded nodes and run time.

翻译：我们把单向和双向超光速搜索和旅行销售商问题近似算法的理念结合起来,为多目标路径搜索问题制定一个新的框架(MGPF ), 提供2种接近的保证。 MGPF旨在找到一条从一个来源到一个目的地的成本最低的路径,以便至少沿途访问一次特定目标的每个节点。 我们提出了数字结果,以说明我们的框架在扩大节点和运行时间方面比常规替代框架的优势。