• DocumentCode
    239388
  • Title

    Multi-scenario optimization using multi-criterion methods: A case study on Byzantine agreement problem

  • Author

    Ling Zhu ; Deb, Kaushik ; Kulkarni, Santosh

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Michigan State Univ., East Lansing, MI, USA
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    2601
  • Lastpage
    2608
  • Abstract
    In this paper, we address solution methodologies of an optimization problem under multiple scenarios. Often in practice, a problem needs to be considered for different scenarios, such as evaluating for different loading conditions, different blocks of data, multi-stage operations, etc. After reviewing various single-objective aggregate methods for handling objectives and constraints under multiple scenarios, we then suggest a multi-objective optimization approach for solving multi-scenario optimization problems. On a Byzantine agreement problem, we demonstrate the usefulness of the proposed multi-objective approach and explain the reasons for their superior behavior. The suggested procedure is generic and now awaits further applications to more challenging problems from engineering and computational fields.
  • Keywords
    fault tolerance; optimisation; Byzantine agreement problem; multicriterion methods; multiobjective optimization approach; multiscenario optimization; single-objective aggregate methods; Aggregates; Context; Linear programming; Loading; Minimization; Optimization; Standards;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2014 IEEE Congress on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6626-4
  • Type

    conf

  • DOI
    10.1109/CEC.2014.6900637
  • Filename
    6900637