A parallel branch and bound algorithm for solving large asymmetric traveling salesman problems

Authors:
J. F. Pekny;D. L. Miller
Affiliations:
Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA;Central Research and Development Department, E. I. du Pont de Nemours & Company Inc., Wilmington, DE
Venue:
CSC '90 Proceedings of the 1990 ACM annual conference on Cooperation
Year:
1990

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Algorithms for the solution of the optimal cost and bottle-neck travelingsalesman problems.

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Abstract

A parallel branch and bound algorithm that solves the asymmetric traveling salesman problem to optimality is described. The algorithm uses an assignment problem based lower bounding technique, subtour elimination branching rules, and a subtour patching algorithm as an upper bounding procedure. The algorithm is organized around a new data flow framework for parallel branch and bound. Computational results are presented for problem sizes from 500 to 7500 cities with cost matrix elements randomly drawn from a uniform distribution of integers in the range [0,1000] and [0,10000].