Branch-and-bound and objective branching with three or more objectives

Nicolas Forget*, Sune Lauth Gadegaard, Kathrin Klamroth, Lars Relund Nielsen, Anthony Przybylski

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

11 Citations (Scopus)
25 Downloads (Pure)

Abstract

The recent success of bi-objective Branch-and-Bound (B&B) algorithms heavily relies on the efficient computation of upper and lower bound sets. These bound sets are used as a supplement to the classical dominance test to improve the computational time by imposing inequalities derived from (partial) dominance in the objective space. This process is called objective branching since it is mostly applied when generating child nodes. In this paper, we extend the concept of objective branching to multi-objective integer optimization problems with three or more objective functions. Several difficulties arise in this case, as there is no longer a lexicographic order among non-dominated outcome vectors when there are three or more objectives. We discuss the general concept of objective branching in any number of dimensions and suggest a merging operation of local upper bounds to avoid the generation of redundant sub-problems. Finally, results from extensive experimental studies on several classes of multi-objective optimization problems is reported.

Original languageEnglish
Article number106012
JournalComputers and Operations Research
Volume148
Number of pages16
ISSN0305-0548
DOIs
Publication statusPublished - Dec 2022

Keywords

  • Bound sets
  • Branch & bound
  • Multi-objective combinatorial optimization
  • Multi-objective integer programming
  • Objective branching

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