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Modeling Design Exploration as Co‐Evolution
Author(s) -
Maher Mary Lou,
Poon Josiah
Publication year - 1996
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/j.1467-8667.1996.tb00323.x
Subject(s) - fitness function , computer science , genetic algorithm , function (biology) , population , conceptual design , machine learning , human–computer interaction , demography , evolutionary biology , sociology , biology
Most computer‐based design tools assume that designers work with a well‐defined problem. However, this assumption has been challenged by current research. The explorative aspect of design, especially during conceptual design, is not fully addressed. This paper introduces a model for problem‐design exploration and how this model can be implemented using the genetic algorithm (GA) paradigm. The basic GA, which does not support our exploration model, evaluates individuals from a population of design solutions with an unchanged fitness function. This approach to evaluation implements search with a prefixed goal. Modifications to the basic GA are required to support exploration. Two approaches to implement a co‐evolving GA are presented and discussed in this paper: one in which the fitness function is represented within the genotype, and a second in which the fitness function is modeled as a separately evolving population of genotypes.