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Multi-Objective Branch and Bound

In: Non-Convex Multi-Objective Optimization

Author

Listed:
  • Panos M. Pardalos

    (University of Florida
    Research University Higher School of Economics)

  • Antanas Žilinskas

    (Vilnius University)

  • Julius Žilinskas

    (Vilnius University)

Abstract

Branch and bound branch and bound approaches for optimization problems were developed in the 1960s [114, 121]. The main concept of a branch and bound algorithm is to detect and discard sets of feasible decisions which cannot contain optimal decisions. The search process can be illustrated as a search tree with the root corresponding to the search space and branches corresponding to its subsets. An iteration of the algorithm processes a node in the search tree that represents an unexplored subset of feasible decisions. The iteration has three main components: selection of the subset to be processed, branching corresponding to subdivision of the subset, and bound calculation.

Suggested Citation

  • Panos M. Pardalos & Antanas Žilinskas & Julius Žilinskas, 2017. "Multi-Objective Branch and Bound," Springer Optimization and Its Applications, in: Non-Convex Multi-Objective Optimization, chapter 0, pages 45-56, Springer.
    • Handle: RePEc:spr:spochp:978-3-319-61007-8_5
    DOI: 10.1007/978-3-319-61007-8_5
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