Optimizing Long-Term Bank Financial Products Portfolio Problems with a Multiobjective Evolutionary Approach

<table class="algorithm-group"><tr><td><table class="algorithm" id="alg1"><tr><td>(1)</td><td><b>for </b><i>t</i> = 1 to <i>T </i><b>do</b></td></tr><tr><td>(2)</td><td> <b>for </b><i>n</i> = 1 to <i>N </i><b>do</b></td></tr><tr><td>(3)</td><td>  Generate <svg height="9.48819pt" id="M62" style="vertical-align:-0.1802893pt" version="1.1" viewbox="-0.0498162 -9.3079 24.5269 9.48819" width="24.5269pt" 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="M181 342V451C133 431 89 419 40 411V388C98 381 102 377 102 311V104C102 38 95 32 33 26V0H263V26C186 32 181 38 181 104V287C203 343 235 372 261 372C277 372 289 366 304 352C310 346 318 345 330 350C349 359 362 379 362 399C362 422 338 449 304 449C256 449 213 393 183 342H181Z"></path></g><g transform="matrix(.013,0,0,-0.013,4.823,0)"><path d="M433 39L423 65C413 59 399 54 387 54C370 54 352 69 352 114V299C352 352 342 392 307 422C285 440 255 449 225 449C168 437 102 399 75 379C56 365 44 353 44 339C44 315 69 296 87 296C101 296 111 303 116 319C124 349 133 371 145 385C156 397 171 404 190 404C241 404 275 364 275 291V274C253 256 180 229 120 209C65 190 39 159 39 110C39 47 88 -12 159 -12C189 -12 237 25 277 52C282 35 288 21 301 8C312 -3 333 -12 348 -12L433 39ZM275 84C256 65 221 48 195 48C164 48 124 73 124 124C124 161 146 180 185 198C206 208 254 229 275 240V84Z"></path></g><g transform="matrix(.013,0,0,-0.013,10.413,0)"><path d="M524 0V26C466 32 460 36 460 104V297C460 393 411 449 331 449C302 449 276 437 248 419C223 402 201 387 181 372V451C137 432 90 420 42 411V388C96 378 102 374 102 310V104C102 38 97 33 29 26V0H246V26C187 32 181 36 181 104V339C211 365 250 390 290 390C357 390 381 345 381 276V109C381 40 374 32 315 26V0H524Z"></path></g><g transform="matrix(.013,0,0,-0.013,17.471,0)"><path d="M517 51L485 54C448 58 441 63 441 115V712C404 700 337 684 285 678V653C357 648 362 645 362 580V437C339 446 309 449 295 449C159 449 38 340 38 201C38 61 143 -12 223 -12C234 -12 261 -6 301 17L362 53V-12C420 9 495 22 517 26V51ZM362 85C338 67 301 51 266 51C201 51 128 109 128 228C128 373 212 411 259 411C296 411 338 395 362 360V85Z"></path></g></svg> from [0, 1]</td></tr><tr><td>(4)</td><td>  <b>if </b><svg height="13.0518pt" id="M63" style="vertical-align:-3.743899pt" version="1.1" viewbox="-0.0498162 -9.3079 183.379 13.0518" width="183.379pt" 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="M181 342V451C133 431 89 419 40 411V388C98 381 102 377 102 311V104C102 38 95 32 33 26V0H263V26C186 32 181 38 181 104V287C203 343 235 372 261 372C277 372 289 366 304 352C310 346 318 345 330 350C349 359 362 379 362 399C362 422 338 449 304 449C256 449 213 393 183 342H181Z"></path></g><g transform="matrix(.013,0,0,-0.013,4.823,0)"><path d="M433 39L423 65C413 59 399 54 387 54C370 54 352 69 352 114V299C352 352 342 392 307 422C285 440 255 449 225 449C168 437 102 399 75 379C56 365 44 353 44 339C44 315 69 296 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transform="matrix(.013,0,0,-0.013,168.347,0)"><path d="M298 36L289 62C276 55 253 45 228 45C202 45 169 60 169 141V397H276C289 405 292 426 282 437H169V574L155 576L90 509V437H45L17 408L21 397H90V107C90 28 125 -12 188 -12C198 -12 213 -8 230 1L298 36Z"></path></g><g transform="matrix(.013,0,0,-0.013,172.351,0)"><path d="M478 437H297V411C355 404 361 392 349 355C329 292 285 174 257 106L167 356C153 394 158 404 205 411L204 437H2V411C57 404 66 391 88 336C117 265 162 144 202 30C208 13 209 0 204 -15C199 -28 191 -49 173 -84C149 -128 130 -153 98 -172C81 -184 73 -193 73 -209C73 -233 101 -257 129 -257C143 -257 156 -252 161 -232C175 -179 197 -122 264 38C333 203 364 286 390 339C417 395 425 403 478 411V437Z"></path></g><g transform="matrix(.013,0,0,-0.013,178.719,0)"><path d="M275 270C275 450 212 609 64 710L45 686C145 604 203 442 203 270S147 -63 45 -147L64 -170C213 -68 275 89 275 270Z"></path></g></svg><b> then</b></td></tr><tr><td>(5)</td><td>   Apply BLX-<svg height="6.1673pt" id="M64" style="vertical-align:-0.2063904pt" version="1.1" viewbox="-0.0498162 -5.96091 7.51131 6.1673" width="7.51131pt" 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="M545 106L524 126C493 85 467 65 455 65C438 65 427 113 405 238C448 295 498 362 543 439L533 448L478 435C453 386 423 331 398 295H395C370 404 347 448 282 448C169 448 23 309 23 153C23 54 65 -12 128 -12C203 -12 283 70 339 155H341C360 29 380 -12 411 -12C444 -12 491 11 545 106ZM333 204C265 95 210 54 169 54C137 54 113 96 113 171C113 302 191 405 252 405C301 405 318 306 333 204Z"></path></g></svg>/SBX crossover operator on element <svg height="9.23375pt" id="M65" style="vertical-align:-3.27284pt" version="1.1" viewbox="-0.0498162 -5.96091 14.4411 9.23375" width="14.4411pt" 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="M483 97L471 123C436 91 401 65 392 65C388 65 384 74 390 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276V109C381 40 374 32 315 26V0H524Z"></path></g></svg></td></tr><tr><td>(6)</td><td>   <b>end if</b></td></tr><tr><td>(7)</td><td>  <b>end for</b></td></tr><tr><td>(8)</td><td><b>end for</b></td></tr></table></td></tr></table>

<div>The procedure of crosssover operator for real-valued matrix.</div>

Complexity

alg1

Algorithm 1

Algorithm 1: Optimizing Long-Term Bank Financial Products Portfolio Problems with a Multiobjective Evolutionary Approach 