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• W2767926929 abstract "Taxi plays an important role in public transportation. However, in real life, it usually takes a long time for passengers to wait for an unoccupied taxi, while number of no-load taxi is very high. Optimized scheme is required to handle global taxi dispatching. The paper presents a novel method of taxi dispatching based on Artificial Fish Swarm Algorithm (AFSA). To avoid slow convergence and falling into local optimum, standard AFSA is improved using strategies of optimizing visual range, step size and swimming behavior. We compare our improved algorithm with standard AFSA and Particle Swarm Optimization through the evaluation with real data of GPS trajectory of 12,000 taxis in Beijing and make performance analysis of effects of parameter configuration to dispatching algorithm. The experimental results show good effectiveness of our method." @default.
• W2767926929 created "2017-11-17" @default.
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• W2767926929 date "2017-01-01" @default.
• W2767926929 modified "2023-09-23" @default.
• W2767926929 title "Intelligent Taxi Dispatching Based on Improved Artificial Fish Swarm Algorithm" @default.
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• W2767926929 doi "https://doi.org/10.1007/978-3-319-69781-9_10" @default.
• W2767926929 hasPublicationYear "2017" @default.
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