Constructing large feasible suboptimal intervals for constrained nonlinear optimization

Tibor Csendes, Zelda B. Zabinsky, Birna P. Kristinsdottir

Research output: Contribution to journalArticle

4 Citations (Scopus)


An algorithm for finding a large feasible n-dimensional interval for constrained global optimization is presented. The n-dimensional interval is iteratively enlarged about a seed point while maintaining feasibility. An interval subdivision method may be used to check feasibility of the growing box. The resultant feasible interval is constrained to lie within a given level set, thus ensuring it is close to the optimum. The ability to determine such a feasible interval is useful for exploring the neighbourhood of the optimum, and can be practically used in manufacturing considerations. The numerical properties of the algorithm are tested and demonstrated by an example problem.

Original languageEnglish
Pages (from-to)279-293
Number of pages15
JournalAnnals of Operations Research
Issue number4
Publication statusPublished - Jul 1 1995


  • AMS subject classification: 90C30, 65K05
  • Constrained nonlinear optimization
  • inclusion function
  • interval arithmetic
  • sensitivity analysis

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Management Science and Operations Research

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