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http://hdl.handle.net/1942/17635
Title: | Theory and practice in large carpooling problems | Authors: | Hartman, I. Keren, D. Abu Dbai, A. Cohan, E. KNAPEN, Luk YASAR, Ansar JANSSENS, Davy |
Issue Date: | 2014 | Publisher: | Elsevier Science BV | Source: | Shakshuki, Elhadi; Yasar, Ansar (Ed.). The 5th International Conference on Ambient Systems, Networks and Technologies (ANT-2014), the 4th International Conference on Sustainable Energy Information Technology (SEIT-2014), Elsevier Science BV, p. 339-347 | Series/Report: | Procedia Computer Science | Series/Report no.: | 32 | Abstract: | We address the carpooling problem as a graph-theoretic problem. If the set of drivers is known in advance, then for any car capacity, the problem is equivalent to the assignment problem in bipartite graphs. Otherwise, when we do not know in advance who will drive their vehicle and who will be a passenger, the problem is NP-hard. We devise and implement quick heuristics for both cases, based on graph algorithms, as well as parallel algorithms based on geometric/algebraic approach. We compare between the algorithms on random graphs, as well as on real, very large, data. | Notes: | [Hartman, Irith Ben-Arroyo; Keren, Daniel; Abu Dbai, Abed; Cohen, Elad] Univ Haifa, Dept Comp Sci, IL-3498838 Haifa, Israel. [Hartman, Irith Ben-Arroyo] Univ Haifa, Caesarea Rothschild Inst, IL-3498838 Haifa, Israel. [Knapen, Luk; Yasar, Ansar-Ul-Haque; Janssens, Davy] Hasselt Univ, Transportat Res Inst IMOB, B-3950 Diepenbeek, Belgium. | Keywords: | Carpooling;Linear Programming;Maximum Weighted Matching;Star Partition Problem;Gradient Projection Algorithm;Scalability;Incremental Algorithms | Document URI: | http://hdl.handle.net/1942/17635 | Link to publication/dataset: | http://www.sciencedirect.com/science/article/pii/S1877050914006334# | ISSN: | 1877-0509 | DOI: | 10.1016/j.procs.2014.05.433 | ISI #: | 000361562600041 | Rights: | 2014 Published by Elsevier B.V. Open access under CC BY-NC-ND license. | Category: | C1 | Type: | Proceedings Paper | Validations: | ecoom 2016 |
Appears in Collections: | Research publications |
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