Parallel Algorithm Design for Branch and Bound

  • David A. Bader
  • William E. Hart
  • Cynthia A. Phillips
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 76)


Large and/or computationally expensive optimization problems sometimes require parallel or high-performance computing systems to achieve reasonable running times. This chapter gives an introduction to parallel computing for those familiar with serial optimization. We present techniques to assist the posting of serial optimization codes to parallel systems and discuss more fundamentally parallel approaches to optimization. We survey the state-of-the-art in distributed and shared-memory architectures and give an overview of the programming models appropriate for efficient algorithms on these platforms. As concrete examples, we discuss the design of parallel branch-and-bound algorithms for mixed-integer programming on a distributed-memory system, quadratic assignment problem on a grid architecture, and maximum parsimony in evolutionary trees on a sharedmemory system.


parallel algorithms optimization branch and bound distributed memory shared memory grid computing 


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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • David A. Bader
    • 1
  • William E. Hart
    • 2
  • Cynthia A. Phillips
    • 2
  1. 1.Department of Electrical & Computer EngineeringUniversity of New MexicoUSA
  2. 2.Discrete Mathematics and Algorithms DepartmentSandia National LaboratoriesUSA

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