• Title of article

    Mutual benefits of two multicriteria analysis methodologies: A case study for batch plant design

  • Author/Authors

    Azzaro-Pantel، نويسنده , , Catherine and Zaraté، نويسنده , , Pascale، نويسنده ,

  • Pages
    11
  • From page
    546
  • To page
    556
  • Abstract
    This paper presents a MultiObjective Genetic Algorithm (MOGA) optimization framework for batch plant design. For this purpose, two approaches are implemented and compared with respect to three criteria, i.e., investment cost, equipment number and a flexibility indicator based on work in process (the so-called WIP) computed by use of a discrete-event simulation model. The first approach involves a genetic algorithm in order to generate acceptable solutions, from which the best ones are chosen by using a Pareto Sort algorithm. The second approach combines the previous Genetic Algorithm with a multicriteria analysis methodology, i.e., the Electre method in order to find the best solutions. The performances of the two procedures are studied for a large-size problem and a comparison between the procedures is then made.
  • Keywords
    Multiobjective Optimization , Batch plant design , Multicriteria decision analysis , genetic algorithm
  • Journal title
    Astroparticle Physics
  • Record number

    2046509