Tracking Moving Optima Using Kalman-Based Predictions Articles uri icon

publication date

  • April 2008

start page

  • 1

end page

  • 30


  • 1


  • 16

International Standard Serial Number (ISSN)

  • 1063-6560

Electronic International Standard Serial Number (EISSN)

  • 1530-9304


  • The dynamic optimization problem concerns finding an optimum in a changing environment. In the field of evolutionary algorithms, this implies dealing with a time-changing fitness landscape. In this paper we compare different techniques for integrating motion information into an evolutionary algorithm, in the case it has to follow a time-changing optimum, under the assumption that the changes follow a nonrandom law. Such a law can be estimated in order to improve the optimum tracking capabilities of the algorithm. In particular, we will focus on first order dynamical laws to track moving objects. A vision-based tracking robotic application is used as testbed for experimental comparison.