Global optimization versus integer programming in portfolio optimization under nonconvex transaction costs

Hiroshi Konno, Rei Yamamoto

Research output: Contribution to journalArticle

23 Citations (Scopus)


This paper is concerned with a portfolio optimization problem under concave and piecewise constant transaction cost. We formulate the problem as nonconcave maximization problem under linear constraints using absolute deviation as a measure of risk and solve it by a branch and bound algorithm developed in the field of global optimization. Also, we compare it with a more standard 0-1 integer programming approach. We will show that a branch and bound method elaborating the special structure of the problem can solve the problem much faster than the state-of-the integer programming code.

Original languageEnglish
Pages (from-to)207-219
Number of pages13
JournalJournal of Global Optimization
Issue number2
Publication statusPublished - 2005 Jun 1



  • 0-1 integer programming
  • Branch and bound algorithm
  • Global optimization
  • Nonconvex transaction cost
  • Portfolio optimization

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research
  • Control and Optimization
  • Applied Mathematics

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