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Abstract

Traffic congestion is a main issue all over the world. For that a proposed system called carpool is introduced. This system that will increase the number of occupation seats by decreasing the number of empty seats. In carpooling, drivers share their vehicles with one or more additional riders whose destinations are similar. It is good to traffic congestion, but also an environmentally sound transportation method. The genetic Algorithm is used for matching of which seekers goes with which driver. A Genetic algorithm is used for large number of users, so it gives proper match. This algorithm can because of exit from local optimal and with high percent produce the problem’s optimal answer. The probability of results show that mooted algorithm has better performance regards as other clustering algorithms specially in two indices, the carefulness of clustering and the quality of clustering.

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How to Cite
R.Kavitha, B.Keerthana, N. Gokulpriya, & R. Aravinthrajan. (2018). A Scalable Approach for Data-Driven Taxi Ride Sharing . International Journal of Intellectual Advancements and Research in Engineering Computations, 6(2), 1838–1844. Retrieved from https://ijiarec.com/ijiarec/article/view/745