Crossover can be constructive when computing unique input–output sequences

Research output: Contribution to journalArticle

Colleges, School and Institutes

Abstract

Unique input-output (UIO) sequences have important applications in conformance testing of finite state machines (FSMs). Previous experimental and theoretical research has shown that evolutionary algorithms (EAs) can compute UIOs efficiently on many FSM instance classes, but fail on others. However, it has been unclear how and to what degree EA parameter settings influence the runtime on the UIO problem. This paper investigates the choice of acceptance criterion in the (1 + 1) EA and the use of crossover in the (mu + 1) Steady State Genetic Algorithm. It is rigorously proved that changing these parameters can reduce the runtime from exponential to polynomial for some instance classes of the UIO problem.

Details

Original languageEnglish
Pages (from-to)1675-1687
Number of pages13
JournalSoft Computing
Volume15
Issue number9
Early online date9 Jun 2010
Publication statusPublished - 1 Sep 2011

Keywords

  • Unique input-output sequences, Crossover operator, Evolutionary algorithms, Finite state machines, Runtime analysis