Evaluation of a Parallel Branch-and-Bound Algorithm on a Class of Multiprocessors

Myung K. Yang, Chita R. Das

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


In this paper, we propose and evaluate a parallel “decomposite best-first” search branch-and-bound algorithm (dbs) for MIN-based multiprocessor systems. We start with a new probabilistic model to estimate the number of evaluated nodes for a serial best-first search branch-and-bound algorithm. This analysis is used in predicting the parallel algorithm speed-up. The proposed algorithm initially decomposes a problem into N subproblems, where N is the number of processors available in a multiprocessor. Afterwards, each processor executes the serial best-first search to find a local feasible solution. Local solutions are broadcasted through the network to compute the final solution. A conflict-free mapping scheme, known as the step-by-step spread, is used for subproblem distribution on the MIN. A speed-up expression for the parallel algorithm is then derived using the serial best-first search node evaluation model. Our analysis considers both computation and communication overheads for providing realistic speed-up. Communication modeling is also extended for the parallel global best-first search technique. All the analytical results are validated via simulation. For large systems, when communication overhead is taken into consideration, it is observed that the parallel decomposite best-first search algorithm provides better speed-up compared to other reported schemes.

Original languageEnglish (US)
Pages (from-to)74-86
Number of pages13
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number1
StatePublished - Jan 1994

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics


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