Evolution Strategies and Composed Test Functions

نویسندگان

  • I. De Falco
  • R. Del Balio
  • A. Della Cioppa
چکیده

| Classical test functions known as F1 to F10 are often used as a benchmark for heuristic optimisation techniques. Recently it has been remarked in literature that relying on the results obtained for their optimisation may be improper or even misleading to assess the eeciency of a technique with respect to others, and a method for developing new more reliable test functions has been given. In this paper a well known class of heuristic strategies, the Evolution Strategies, is considered for the solution of one such function and its results are compared against those obtained by classical discrete Genetic Algorithms, adaptive search strategies and hill{climbing methods.

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تاریخ انتشار 2007