On the convergence of a population-based global optimization algorithm

Ş Ilker Birbil, Shu Cherng Fang, Ruey Lin Sheu

Research output: Contribution to journalArticlepeer-review

160 Citations (Scopus)


In global optimization, a typical population-based stochastic search method works on a set of sample points from the feasible region. In this paper, we study a recently proposed method of this sort. The method utilizes an attraction-repulsion mechanism to move sample points toward optimality and is thus referred to as electromagnetism-like method (EM). The computational results showed that EM is robust in practice, so we further investigate the theoretical structure. After reviewing the original method, we present some necessary modifications for the convergence proof. We show that in the limit, the modified method converges to the vicinity of global optimum with probability one.

Original languageEnglish
Pages (from-to)301-318
Number of pages18
JournalJournal of Global Optimization
Issue number2-3
Publication statusPublished - 2004 Nov

All Science Journal Classification (ASJC) codes

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


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