A Driver-Centric Carpooling: Optimal Route-Finding Model Using Heuristic Multi-Objective Search

摘要

century. To ease the severity of this problem, `Road-Space Rationing' has been adopted by many countries. Carpooling service, also known as ride-sharing, is a by-product of `Road-Space Rationing' feature. With intelligent carpooling service, people can share rides more elegantly by maximizing the seat occupancy rate. In this paper, we introduce an efficient carpooling system that can provide the optimal route for a driver. To find the optimal route we use the Non-Dominated Genetic Sorting Algorithm (NSGA). In case of multiple near-optimal results, we Figure out a single result by applying the proposed Crowding Distance Sorting Algorithm (CDSA). Finally, we show the comparison between each of the selected objectives and the optimal result. Our comparison shows that the optimal outcome has a minimum trade-off in respect of all individual objective best results.