A Probability Collectives Approach with a Feasibility-Based Rule for Constrained Optimization

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="980216.fig.009a" src="https://static.hindawi.com/articles/acisc/volume-2011/980216/figures/980216.fig.009a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>A case for voting heuristic</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="980216.fig.009b" src="https://static.hindawi.com/articles/acisc/volume-2011/980216/figures/980216.fig.009b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Voting grids</td></tr></table></td></tr></table>

Applied Computational Intelligence and Soft Computing

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Figure 9

Figure 9: A Probability Collectives Approach with a Feasibility-Based Rule for Constrained Optimization 