MOEA Parallelization

  • Carlos A. Coello Coello
  • David A. Van Veldhuizen
  • Gary B. Lamont
Part of the Genetic Algorithms and Evolutionary Computation book series (GENA, volume 5)

Abstract

When solving optimization problems, parallelizing associated computer algorithms may result in more efficient, and possibly more effective, implementations. This is primarily due to the increased number of processors (and local memories) working on the problem, thus allowing investigation of more of the solution space in a given time period.

Keywords

Parallel Implementation Objective Function Evaluation Interprocessor Communication Numeric Optimization Problem Slave Processor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Carlos A. Coello Coello
    • 1
  • David A. Van Veldhuizen
    • 2
  • Gary B. Lamont
    • 3
  1. 1.CINVESTAV-IPNMexicoMexico
  2. 2.Air Force Research LaboratoryBrooks Air Force BaseUSA
  3. 3.Air Force Institute of TechnologyDaytonUSA

Personalised recommendations