Implementation of Approximation Algorithms for Weighted and Unweighted Edge-Disjoint Paths in Bidirected Trees

Given a set of weighted directed paths in a bidirected tree, the maximum weight edge-disjoint paths problem (MWEDP) is to select a subset of the given paths such that the selected paths are edge-disjoint and the total weight of the selected paths is maximized. MWEDP is NP-hard for bidirected trees of arbitrary degree, even if all weights are the same (the unweighted case). Three different approximation algorithms are implemented: a known combinatorial (5/3 + Ɛ)-approximation algorithm A1 for the unweighted case, a new combinatorial 2-approximation algorithm A2 for the weighted case, and a known (5/3 + Ɛ)-approximation algorithm A3 for the weighted case that is based on linear programming. For algorithm A1, it is shown how efficient data structures can be used to obtain a worst-case running-time of O(m+n+41/Ɛ√nċm) for instances consisting of m paths in a tree with n nodes. Experimental results regarding the running-times and the quality of the solutions obtained by the three approximation algorithms are reported. Where possible, the approximate solutions are compared to the optimal solutions, which were computed by running CPLEX on an integer linear programming formulation of MWEDP.

[1]  Piotr Berman,et al.  Improvements in throughout maximization for real-time scheduling , 2000, STOC '00.

[2]  Jon M. Kleinberg,et al.  Approximation algorithms for disjoint paths problems , 1996 .

[3]  Thomas Erlebach Scheduling connections in fast networks , 1999 .

[4]  Klaus Jansen,et al.  Maximizing the Number of Connections in Optical Tree Networks , 1998, ISAAC.

[5]  Sudipto Guha,et al.  Approximating the throughput of multiple machines under real-time scheduling , 1999, STOC '99.

[6]  Sudipto Guha,et al.  Approximating the Throughput of Multiple Machines in Real-Time Scheduling , 2002, SIAM J. Comput..

[7]  Piotr Berman,et al.  Multi-phase Algorithms for Throughput Maximization for Real-Time Scheduling , 2000, J. Comb. Optim..

[8]  Mihalis Yannakakis,et al.  Primal-Dual Approximation Algorithms for Integral Flow and Multicut in Trees, with Applications to Matching and Set Cover , 1993, ICALP.

[9]  Klaus Jansen,et al.  An optimal greedy algorithm for wavelength allocation in directed tree networks , 1997, Network Design: Connectivity and Facilities Location.

[10]  Kurt Mehlhorn,et al.  LEDA: a platform for combinatorial and geometric computing , 1997, CACM.

[11]  Reuven Bar-Yehuda,et al.  A unified approach to approximating resource allocation and scheduling , 2001, JACM.

[12]  Uzi Vishkin,et al.  On Finding Lowest Common Ancestors: Simplification and Parallelization , 1988, AWOC.

[13]  Venkatesan Guruswami,et al.  Near-optimal hardness results and approximation algorithms for edge-disjoint paths and related problems , 1999, STOC '99.

[14]  Éva Tardos,et al.  Disjoint paths in densely embedded graphs , 1995, Proceedings of IEEE 36th Annual Foundations of Computer Science.

[15]  Klaus Jansen,et al.  The Maximum Edge-Disjoint Paths Problem in Bidirected Trees , 2001, SIAM J. Discret. Math..

[16]  Klaus Jansen,et al.  Optimal Wavelength Routing on Directed Fiber Trees , 1999, Theor. Comput. Sci..

[17]  Richard M. Karp,et al.  A n^5/2 Algorithm for Maximum Matchings in Bipartite Graphs , 1971, SWAT.

[18]  Klaus Jansen,et al.  Efficient implementation of an optimal greedy algorithm for wavelength assignment in directed tree networks , 1999, JEAL.