EvoArch: An evolutionary algorithm for architectural layout design

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "Samuel S. Y. Wong and Keith C. C. Chan",
  title =        "{EvoArch:} An evolutionary algorithm for architectural
                 layout design",
  journal =      "Computer-Aided Design",
  volume =       "41",
  number =       "9",
  pages =        "649--667",
  year =         "2009",
  ISSN =         "0010-4485",
  DOI =          "doi:10.1016/j.cad.2009.04.005",
  URL =          "http://www.sciencedirect.com/science/article/B6TYR-4W6XW17-2/2/8b37ad1171b7fd66aaeb17f58baf7ee0",
  keywords =     "genetic algorithms, genetic programming, Architectural
                 space topology, Evolutionary algorithm, Crossover,
                 Graph algorithm, Mutation",
  abstract =     "The architectural layout design problem, which is
                 concerned with the finding of the best adjacencies
                 between functional spaces among many possible ones
                 under given constraints, can be formulated as a
                 combinatorial optimisation problem and can be solved
                 with an Evolutionary Algorithm (EA). We present
                 functional spaces and their adjacencies in form of
                 graphs and propose an EA called EvoArch that works with
                 a graph-encoding scheme. EvoArch encodes topological
                 configuration in the adjacency matrices of the graphs
                 that they represent and its reproduction operators
                 operate on these adjacency matrices. In order to
                 explore the large search space of graph topologies,
                 these reproduction operators are designed to be
                 unbiased so that all nodes in a graph have equal
                 chances of being selected to be swapped or mutated. To
                 evaluate the fitness of a graph, EvoArch makes use of a
                 fitness function that takes into consideration
                 preferences for adjacencies between different
                 functional spaces, budget and other design constraints.
                 By means of different experiments, we show that EvoArch
                 can be a very useful tool for architectural layout
                 design tasks.",

Genetic Programming entries for Samuel S Y Wong Keith C C Chan