• Definition


    Multi-objective evolutionary algorithms (MOEAs) are any of the paradigms of evolutionary computing (e.g., genetic algorithms, evolutionary strategies, etc.) used to solve problems requiring optimization of two or more potentially conflicting objectives, without resorting to the reduction of the objectives to a single objective by the means of a weighted sum.

  • Detailed Description


    The main ideas of evolutionary algorithms (EAs) are derived from the principles of variation and selection that are the foundation of Darwinian evolution (Beyer ). An evolutionary algorithm operates on a population of individuals, every one of which represents a candidate solution to a given optimization problem. Each individual is assigned a fitness value, which represents the “quality” of that potential solution. Solutions evolve by replication and become...


GH_C : pachyderm

  • outil d’aide à la décision a priori de la forme architecturale, utilisant un algorithme génétique multicritère couplé à un système de simulation acoustique et de calcul des mesures ISO. Son utilisation permet au concepteur l’émersion de morphologies innovantes et qualitatives, aptes à mettre en espace les visions contemporaines des espaces de performance.


    Hamdy, Mohamed, Anh-Tuan Nguyen, and Jan L.M. Hensen. 2016. "A performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems." Energy and Buildings 121: 57–71. https://doi.org/10.1016/j.enbuild.2016.03.035.
    Vierlinger, Robert. 2013. "Multi Objective Design Interface." https://doi.org/10.13140/RG.2.1.3401.0324.
    Vierlinger, Robert, and Klaus Bollinger. 2014. "Accomodating Change in Parametric Design." https://doi.org/10.13140/RG.2.1.2827.5922.
    Gerber, David Jason, Rodrigo Shiordia, Sreerag Veetil, and Arjun Mahesh. 2014. “Design Agency: Prototyping Multi-Agent System Simulation for Design Search and Exploration,” 10.
    Chaszar, Andre. n.d. “Multivariate Interactive Visualization of Data in Generative Design,” 8.


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