Research Area: Evolutionary Systems in Designing


Evolutionary systems provide an interesting and useful model of search and optimization for designers. We have extended genetic algorithms by introducing the concepts of genetic engineering and by changing the evolutionary processes. This has had the effect of producing efficiencies in finding results. More interestingly it has allowed us to produce creative results, results that otherwise could not have been produced by any evolutionary system or other system.

Projects include:

  • genetic engineering extensions to genetic algorithms
  • novel crossover processes in genetic-related algorithms
  • evolution of the representation of style
  • evolution of creative designs




Papers that describe some of the research methods and some of the main fundings:

  • Gero, J. S. and Kazakov, V. (2000) Adaptive enlargement of state spaces in evolutionary designing, AIEDAM 14(1): 31-38. (pdf)
  • Gero, JS and Kazakov, V (2001) A genetic engineering extension to genetic algorithms, Evolutionary Computation 9(1): 71-92 (pdf)

Papers that describe the research in more detail:

  • Ding, L and Gero, JS (2001) The emergence of the representation of style in design, Environment and Planning B: Planning and Design, 28(5):707-731. (pdf)
  • Gero, JS and Kazakov, V (1998) Evolving design genes in space layout problems, Artificial Intelligence in Engineering 12(3):163-176. (pdf)
  • Gero, JS and Kazakov, V (1997) Learning and reusing information in space layout problems using genetic engineering, Artificial Intelligence in Engineering 11(3): 329-334. (pdf).
  • Gero, JS and Louis, S (1995) Improving Pareto optimal designs using genetic algorithms, Microcomputers in Civil Engineering 10(4): 241-249.
  • Gero, JS and Sosa, R (2008) Complexity measures as a basis for mass customisation of novel designs, Environment and Planning B: Planning and Design (to appear) (pdf)
  • Jo, J and Gero, JS (1998) Space layout planning using an evolutionary approach, Artificial Intelligence in Engineering 12(3): 149-162. (pdf)
  • Schnier, T and Gero, JS (1996) Learning representations for creative design using evolution, AIEDAM 10: 175-177.

For the rest you can scour my publications starting with those under In Progress.


The people who have or are working with me on this include:

  • Lan Ding
  • Jun Jo
  • Romuald Jagielski
  • Vladimir Kazakov
  • Sourav Kundu
  • Sushil Louis
  • Thorsten Schnier
  • Ricardo Sosa