The Inertia Weight Updating Strategies in Particle Swarm Optimisation Based on the Beta Distribution

<div>The normalized standard deviation and global best model of 51 runs for f22, f23, f25, and f27; SDEV is the standard deviation, GBEST fitness of global best particle. Note: all values are shifted due to the logarithmic transformation of <svg height="9.7821pt" id="M86" style="vertical-align:-3.57194pt" version="1.1" viewbox="-0.0498162 -6.21016 7.97344 9.7821" width="7.97344pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M556 393C556 426 537 448 514 448C496 448 478 435 471 420C468 414 462 401 466 394C473 382 480 368 480 346C480 268 392 143 338 67H336C329 163 319 253 309 330S286 448 254 448C215 448 160 383 127 337L143 311C167 344 200 373 208 373S222 365 229 320C246 214 264 66 268 -20C219 -83 131 -171 17 -239L25 -261L137 -235C248 -110 273 -79 335 8C384 77 481 215 520 287C544 332 556 363 556 393Z" id="g113-122"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="579" vert-adv-y="579"></glyph.data></g></svg>-axis.</div>

Mathematical Problems in Engineering

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Figure 4

Figure 4: The Inertia Weight Updating Strategies in Particle Swarm Optimisation Based on the Beta Distribution 