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Abstract

In the Finite Capacity Dial-a-Ride problem the input is a metric space, a set of objects {d i }, each specifying a source s i and a destination t i , and an integer k—the capacity of the vehicle used for making the deliveries. The goal is to compute a shortest tour for the vehicle in which all objects can be delivered from their sources to their destinations while ensuring that the vehicle carries at most k objects at any point in time. In the preemptive version an object may be dropped at intermediate locations and picked up later and delivered. Let N be the number of nodes in the input graph. Charikar and Raghavachari [FOCS ’98] gave a min {O(logN),O(k)}-approximation algorithm for the preemptive version of the problem. In this paper has no min {O(log\(^{\rm 1/4-{\it \epsilon}}\) N),k 1 − ε}-approximation algorithm for any ε> 0 unless all problems in NP can be solved by randomized algorithms with expected running time O(n polylog n ).

Keywords

Approximation Algorithm Source Node Travel Salesman Problem Travel Salesman Problem Random String 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Inge Li Gørtz
    • 1
  1. 1.Technical University of Denmark 

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