Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Efficient Algorithms for Finding Maximal Matching in Graphs
CAAP '83 Proceedings of the 8th Colloquium on Trees in Algebra and Programming
Scheduling Algorithm for On-Demand Bus System
ITNG '09 Proceedings of the 2009 Sixth International Conference on Information Technology: New Generations
Towards mobility-based clustering
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
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Ridesharing is a promising method to address transportation problems such as traffic jams and parking. Although traditional carpooling and taxi ridesharing have been investigated by many, slugging, as a simple yet effective form of ridesharing, has not been well-studied. In this paper, we formally define the slugging problem and its generalization. We provide proofs of their computational time complexity. For the variants of the slugging problem that are constrained by the vehicle capacity and travel time delay, we prove NP-completeness and also propose some effective heuristics. In addition, we discuss the dynamic slugging problem. We conducted experiments using a GPS trajectory data set containing 60 thousand trips. The experimental results show that our proposed heuristics can achieve close-to-optimal performances, which means as much as 59% saving in vehicle travel distance.