Algorithm Engineering and Experimentation: Third by Sándor P. Fekete, Henk Meijer, André Rohe, Walter Tietze

By Sándor P. Fekete, Henk Meijer, André Rohe, Walter Tietze (auth.), Adam L. Buchsbaum, Jack Snoeyink (eds.)

This booklet constitutes the completely refereed post-proceedings of the 3rd overseas Workshop on set of rules Engineering and Experimentation, ALENEX 2001, held in Washington, DC, united states in January 2001.
The 15 revised complete papers awarded including the abstracts of 3 invited shows have undergone rounds of reviewing and revision and have been chosen from 31 submissions. one of the subject matters addressed are heuristics for approximation, community optimization, TSP, randomization, sorting, details retrieval, graph computations, tree clustering, scheduling, community algorithms, element set computations, looking out, and knowledge mining.

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Extra info for Algorithm Engineering and Experimentation: Third International Workshop, ALENEX 2001 Washington, DC, USA, January 5–6, 2001 Revised Papers

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In Proc. 2nd Scandinavian Worksh. Algorithm Theory (SWAT), LNCS 447, pages 38–47. Springer, 1990. D. Eppstein. Finding the k shortest paths. SIAM Journal on Computing, 28(2):652–673, 1999. M. Garey and D. Johnson. Computers and Intractibility: A Guide to the Theory of NP-Completeness. W. H. Freeman, New York, 1979. H. Hamacher, J. Picard, and M. Queranne. On finding the k-best cuts in a network. Operations Research Letters, 2(6):303–305, 1984. G. Handler and I. Zang. A Dual Algorithm for the Constrained Shortest Path Problem.

Ziegelmann. Resource constrained shortest paths. In 7th Annual European Symposium on Algorithms (ESA2000), LNCS 1879, pages 326–337, 2000. R. Nygaard, J. Husøy, and D. Haugland. Compression of image contours using combinatorial optimization. In Int. Conf. on Image Processing (ICIP), 1998. G. Xue. Primal-dual algorithms for computing weight-constrained shortest paths and weight-constrained minimum spanning trees. In 19th IEEE International Performance, Computing, and Communications Conference (IPCCC 2000), pages 271–277, 2000.

The Asymmetric Traveling Salesman Problem: Algorithms, Instance Generators, and Tests Jill Cirasella1 , David S. Johnson2 , Lyle A. edu Department of Computer Science, Washington University Box 1045, One Brookings Drive, St. edu Abstract. The purpose of this paper is to provide a preliminary report on the first broad-based experimental comparison of modern heuristics for the asymmetric traveling salesmen problem (ATSP). There are currently three general classes of such heuristics: classical tour construction heuristics such as Nearest Neighbor and the Greedy algorithm, local search algorithms based on re-arranging segments of the tour, as exemplified by the Kanellakis-Papadimitriou algorithm [KP80], and algorithms based on patching together the cycles in a minimum cycle cover, the best of which are variants on an algorithm proposed by Zhang [Zha93].

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