Improvement Analysis and Application of Real-Coded Genetic Algorithm for Solving Constrained Optimization Problems

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static-preview.hindawi.com/articles/mpe/volume-2018/5760841/figures/5760841.fig.006a.svgz" name="5760841.fig.006a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Initial population</td></tr><tr class="fig-image" id="b"><td><object data="https://static-preview.hindawi.com/articles/mpe/volume-2018/5760841/figures/5760841.fig.006b.svgz" name="5760841.fig.006b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>After 5 iterations</td></tr><tr class="fig-image" id="c"><td><object data="https://static-preview.hindawi.com/articles/mpe/volume-2018/5760841/figures/5760841.fig.006c.svgz" name="5760841.fig.006c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>After 10 iterations</td></tr><tr class="fig-image" id="d"><td><object data="https://static-preview.hindawi.com/articles/mpe/volume-2018/5760841/figures/5760841.fig.006d.svgz" name="5760841.fig.006d" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(d) </b>After 15 iterations</td></tr></table>

<div>The evolution of population in IRCGA-2 as a function of the number of iterations.</div>

Mathematical Problems in Engineering

fig6

Figure 6

Figure 6: Improvement Analysis and Application of Real-Coded Genetic Algorithm for Solving Constrained Optimization Problems 