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With the generation of massive data from bus IC cards, how to effectively and efficiently recommend comfortable bus routes to bus passengers is a challenging and complex task. In this paper, waiting time, crowded time, and driving time between different bus stations on different bus routes at different times of the day are calculated from bus IC cards data history. Then, a multi-objective program with various constraints is suggested to recommend comfortable bus routes for bus passengers, and a genetic algorithm is developed to search for expected solutions. The proposed method is implemented using bus IC cards data from Chongqing, China and will be a promising tool for bus passengers when choosing comfortable bus routes.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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