Dynamic Route Optimization With Multi-Category Constraints for POIs Visit

Abstract

In the domain of route planning, the critical concern for travel efficiency has shifted towards optimizing travel time over distance due to the rise in congestion and the dynamic nature of modern road networks. Addressing this shift, we introduce Dynamic Route Optimization with Multi-Category Constraints (DROMC) for Point-of-Interest (POI) visits, which seeks to find the most time-efficient path that satisfies a user-defined list of requirements, considering both the spatial and temporal dimensions. This paper proposes a novel approach that leverages a path enumeration algorithm, which iteratively validates the k-fastest paths until all user queries are satisfied, ensuring adherence to time constraints and POI availability. To enhance the algorithm’s efficiency, we employ several key methodologies. First, we adapt the kSP algorithm to account for POI-focused path enumeration. We also introduce a Shared Prefix Tree (SPFT) with binary encoding, which significantly improves the storage and retrieval of path information. Moreover, we integrate a grid-based heuristic for quicker computation and implement strategic pruning methods to circumvent redundant calculations and manage POI business hours effectively. Our extensive experiments on real-world networks demonstrate the algorithm’s superiority in finding more efficient paths in shorter time frames compared to existing methods.