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Deterministic GO algorithms

In: Introduction to Nonlinear and Global Optimization

Author

Listed:
  • Eligius M. T. Hendrix

    (Málaga University)

  • Boglárka G.-Tóth

    (Budapest University of Technology and Economics)

Abstract

The main concept of deterministic global optimization methods is that in the generic algorithm description (4.1), the next iterate does not depend on the outcome of a pseudo random variable. Such a method gives a fixed sequence of steps when the algorithm is repeated for the same problem. There is not necessarily a guarantee to reach the optimum solution. Many approaches such as grid search, random function approaches and the use of Sobol numbers are deterministic without giving a guarantee. In Section 6.2 we discuss the deterministic heuristic direct followed by the ideas of stochastic models and response surface methods in Section 6.3. After that we will focus on methods reported in the literature that expose the following characteristics.

Suggested Citation

  • Eligius M. T. Hendrix & Boglárka G.-Tóth, 2010. "Deterministic GO algorithms," Springer Optimization and Its Applications, in: Introduction to Nonlinear and Global Optimization, chapter 6, pages 137-170, Springer.
    • Handle: RePEc:spr:spochp:978-0-387-88670-1_6
    DOI: 10.1007/978-0-387-88670-1_6
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