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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. Two-Phase Bilevel Search for the Moving-Target Traveling Salesman Problem with Moving Obstacles

    Researchers have developed a new algorithm called Two-Phase Bilevel Search (TPBS) to tackle the complex Moving-Target Traveling Salesman Problem with Moving Obstacles (MT-TSP-MO). This problem involves an agent navigating to targets within specific time windows while avoiding dynamic obstacles. The proposed TPBS algorithm, along with a Mixed-Integer Conic Programming formulation, significantly outperforms existing methods in terms of success rates, solution costs, and computation time, as demonstrated on instances with up to 40 targets and 40 obstacles. AI

    IMPACT This research could lead to more efficient pathfinding and logistics solutions in dynamic environments.