The lightweight genetic search algorithm: An efficient genetic algorithm for small search range problems
Journal
International Journal of Computational Engineering Science
Journal Volume
5
Journal Issue
3
Pages
639-663
Date Issued
2004
Author(s)
Lin, C.-H.
Abstract
Genetic algorithms have been applied to many optimization and search problems and shown to be very efficient. However, the efficiency of genetic algorithms is not guaranteed in those applications where the search space is small, such as the block motion estimation in video coding applications, or equivalently the chromosome length is relatively short, less than 5 for example. Since the characteristics of these small search space applications are far away from the conventional search problems in which the common genetic algorithms worked well. New treatments of genetic algorithms for dealing with the small range search problems are therefore of interest. In this paper, the efficiency (will be defined later) of the genetic operations of common genetic algorithms, such as crossover and mutation, are analyzed for this special situation. As expected, the so-obtained efficiency/performance of the genetic operations is quite different from that of their traditional counterparts. To fill this gap, a lightweight genetic search algorithm is presented to provide an efficient way for generating near optimal solutions for these kinds of applications. The control overheads of the lightweight genetic search algorithm is very low as compared with that of the conventional genetic algorithms. It is shown by simulations that a lot of computations can be saved by applying the newly proposed algorithm while the search results are still well approved. © Imperial College Press.
Other Subjects
Computational complexity; Computer simulation; Computer vision; Feature extraction; Image coding; Motion estimation; Optimization; Problem solving; Genetic evolution; Genetic search algorithms; Optimal solutions; Search problems; Genetic algorithms
Type
journal article