Parallel Shortest Paths Methods for Globally Optimal Trajectories

D. P. Bertsekas, F. Guerriero, R. Musmanno

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper we consider a special type of trajectory optimization problem that can be viewed as a continuous-space analog of the classical shortest path problem. This problem is approached by space discretization and solution of a discretized version of the associated Hamilton-Jacobi equation. It was recently shown by Tsitsiklis [1] that some of the ideas of classical shortest path methods, such as those underlying Dijkstra's algorithm, can be applied to solve the discretized Hamilton-Jacobi equation. In more recent work, Polymenakos, Bertsekas and Tsitsiklis [2] have carried this analogy further to show that some efficient label correcting methods for shortest path problems, the SLF and SLF/LLL methods of [3] and [4], can be fruitfully adapted to solve the discretized Hamilton-Jacobi equation. In this paper we discuss parallel asynchronous implementations of these methods on a shared memory multiprocessor, the Alliant FX/80. Our results show that these methods are well suited for parallelization and achieve excellent speedup.

Original languageEnglish (US)
Pages (from-to)303-315
Number of pages13
JournalAdvances in Parallel Computing
Volume10
Issue numberC
DOIs
StatePublished - Jan 1 1995
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science(all)

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