• DocumentCode
    2691757
  • Title

    A simultaneous EMO for the solution of the multi-Multi-Objective Optimization Problem

  • Author

    Avigad, Gideon

  • Author_Institution
    Tel Aviv Univ., Tel-Aviv
  • fYear
    2007
  • fDate
    25-28 Sept. 2007
  • Firstpage
    2117
  • Lastpage
    2124
  • Abstract
    In this paper the recently introduced multi-Multi- Objective Optimization Problem (m-MOOP) is solved using a novel ´Simultaneous´ approach. This is in contrast to both the ´Sequential´ approach, which has been introduced previously and to a straightforward solution of the m-MOOP by posing it as a MOOP. The ´Simultaneous´ approach is motivated by the need to overcome the apparent deficiencies of the other approaches. The simultaneous EMO algorithm, which is introduced in order to solve the m-MOOP, possesses several new EC related algorithmic features, including a multi- problem individual and a multi-problem sorting procedure. Formerly presented measures together with a newly introduced one, serve for a comparison between the introduced simultaneous approach with both the sequential approach and with a straightforward implementation of an EMO to an m- MOOP, which is posed as a MOOP. The comparison between the different approaches is practiced by using both academic examples as well as an engineering design example.
  • Keywords
    evolutionary computation; optimisation; m-MOOP problem; multimultiobjective optimization problem; simultaneous EMO algorithm; Evolutionary computation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-1339-3
  • Electronic_ISBN
    978-1-4244-1340-9
  • Type

    conf

  • DOI
    10.1109/CEC.2007.4424734
  • Filename
    4424734