Crossover Method for Interactive Genetic Algorithms to Estimate Multimodal Preferences

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="302573.fig.0014a" src="https://static-preview.hindawi.com/articles/acisc/volume-2013/302573/figures/302573.fig.0014a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>Approximated multimodal landscape (for dotted pattern)</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="302573.fig.0014b" src="https://static-preview.hindawi.com/articles/acisc/volume-2013/302573/figures/302573.fig.0014b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Approximated unimodal landscape (for plaid pattern)</td></tr></table></td></tr></table>

<table>Examples of approximated Kansei landscapes.</table>

Applied Computational Intelligence and Soft Computing

fig14

Figure 14

Figure 14: Crossover Method for Interactive Genetic Algorithms to Estimate Multimodal Preferences 