An Improved Hybrid Algorithm Based on Biogeography/Complex and Metropolis for Many-Objective Optimization

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left">Function</td><td class="align_center"><span style="width: 34.1394ptpx;"><svg height="8.8423pt" id="M221" style="vertical-align:-0.2064009pt" version="1.1" viewbox="-0.0498162 -8.6359 34.1394 8.8423" width="34.1394pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M962 650H795L470 145L347 650H176L170 622C268 613 275 606 244 503L190 322C150 188 132 126 118 91C102 50 80 33 18 28L12 0H245L251 28C175 35 170 48 174 93C177 128 191 180 220 284L292 542H294C331 392 383 150 409 4H432L774 555H776L714 137C700 40 694 34 612 28L606 0H868L874 28C793 34 784 37 797 137L849 533C859 612 863 616 956 622L962 650Z" id="g113-78"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="985" vert-adv-y="985"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,16.439,0)"><path d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z" id="g117-34"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="587" vert-adv-y="587"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,27.702,0)"><path d="M285 378C315 398 338 416 353 432C373 451 384 474 384 503C384 579 325 635 236 635H235C182 635 136 610 108 579L65 516L85 496C110 533 150 575 205 575C258 575 300 543 300 481C300 407 232 369 141 339L147 310C163 315 188 321 211 321C268 321 338 284 338 192C338 94 288 40 217 40C160 40 119 68 93 91C85 98 77 97 69 91C60 84 47 71 46 58C44 46 48 35 62 22C75 10 116 -12 162 -12C234 -12 424 62 424 224C424 297 373 359 285 376V378Z" id="g113-52"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="480" vert-adv-y="480"></glyph.data></g></svg></span></td><td class="align_center"><span style="width: 34.1394ptpx;"><svg height="8.68572pt" id="M222" style="vertical-align:-0.0498209pt" version="1.1" viewbox="-0.0498162 -8.6359 34.1394 8.68572" width="34.1394pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M962 650H795L470 145L347 650H176L170 622C268 613 275 606 244 503L190 322C150 188 132 126 118 91C102 50 80 33 18 28L12 0H245L251 28C175 35 170 48 174 93C177 128 191 180 220 284L292 542H294C331 392 383 150 409 4H432L774 555H776L714 137C700 40 694 34 612 28L606 0H868L874 28C793 34 784 37 797 137L849 533C859 612 863 616 956 622L962 650Z" id="g113-78"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="985" vert-adv-y="985"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,16.439,0)"><path d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z" id="g117-34"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="587" vert-adv-y="587"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,27.702,0)"><path d="M456 178V225H360V632H320C217 496 115 347 20 206V178H280V106C280 40 276 34 189 27V0H445V27C364 34 360 39 360 106V178H456ZM280 225H82C149 335 214 431 278 520H280V225Z" id="g113-53"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="480" vert-adv-y="480"></glyph.data></g></svg></span></td><td class="align_center"><span style="width: 34.1394ptpx;"><svg height="8.8423pt" id="M223" style="vertical-align:-0.2064009pt" version="1.1" viewbox="-0.0498162 -8.6359 34.1394 8.8423" width="34.1394pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M962 650H795L470 145L347 650H176L170 622C268 613 275 606 244 503L190 322C150 188 132 126 118 91C102 50 80 33 18 28L12 0H245L251 28C175 35 170 48 174 93C177 128 191 180 220 284L292 542H294C331 392 383 150 409 4H432L774 555H776L714 137C700 40 694 34 612 28L606 0H868L874 28C793 34 784 37 797 137L849 533C859 612 863 616 956 622L962 650Z" id="g113-78"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="985" vert-adv-y="985"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,16.439,0)"><path d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z" id="g117-34"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="587" vert-adv-y="587"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,27.702,0)"><path d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z" id="g113-54"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="480" vert-adv-y="480"></glyph.data></g></svg></span></td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">DTLZ1</td><td class="align_center">36500</td><td class="align_center">26400</td><td class="align_center">12600</td></tr><tr><td class="align_left">DTLZ2</td><td class="align_center">22840</td><td class="align_center">42500</td><td class="align_center">73600</td></tr><tr><td class="align_left">DTLZ3</td><td class="align_center">92000</td><td class="align_center">14600</td><td class="align_center">220000</td></tr><tr><td class="align_left">DTLZ4</td><td class="align_center">54700</td><td class="align_center">13200</td><td class="align_center">220000</td></tr><tr><td class="align_left">WFG1–9</td><td class="align_center">36500</td><td class="align_center">74300</td><td class="align_center">157500</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Maximum number of fitness evaluation for different function.

Mathematical Problems in Engineering

tab2

Table 2

Table 2: An Improved Hybrid Algorithm Based on Biogeography/Complex and Metropolis for Many-Objective Optimization 