Global Optimization Toolbox User's Guide - MathWorks

More documents

Recommendations

Info

1 Introducing Global Optimization Toolbox Functions 1-26 dimension of the decision variables. ga does not require any starting points, because it takes the dimension of the decision variables as an input. ga can generate its start population automatically. Compare the characteristics of Global Optimization Toolbox solvers to Optimization Toolbox solvers. Solver Convergence Characteristics fmincon, fminunc, fseminf, lsqcurvefit, lsqnonlin Proven quadratic convergence to local optima for smooth problems fminsearch No convergence proof — counterexamples exist. fminbnd Proven convergence to local optima for smooth problems, slower than quadratic. All these Optimization Toolbox solvers: Have deterministic iterates Start from one user-supplied point Search just one basin of attraction Deterministic iterates Gradient-based User-supplied starting point Deterministic iterates No gradients User-supplied start point No constraints Deterministic iterates No gradients Why Are Some Solvers Objects? User-supplied start point Only one-dimensional problems GlobalSearch and MultiStart are objects. What does this mean for you? You create a GlobalSearch or MultiStart object before running your problem. You can reuse the object for running multiple problems.
GlobalSearch and MultiStart objects are containers for algorithms and global options. You use these objects to run a local solver multiple times. The local solver has its own options. Choose a Solver For more information, see the “Object-Oriented Programming” documentation. 1-27
Page 1 and 2: Global Optimization Toolbox User’
Page 3: Revision History January 2004 Onlin
Page 6 and 7: vi Contents 3 How to Write a Functi
Page 8 and 9: viii Contents An Unsuccessful Poll
Page 10 and 11: x Contents 6 Genetic Algorithm Usin
Page 12 and 13: xii Contents 8 9 Bibliography .....
Page 14 and 15: 11 12 A Getting Started xiv Content
Page 16 and 17: 1 Introducing Global Optimization T
Page 44 and 45: 2 Write Files for Optimization Func
Page 54 and 55: 3 Using GlobalSearch and MultiStart
Page 90 and 91:
3 Using GlobalSearch and MultiStart
Page 92 and 93:
Page 94 and 95:
Page 96 and 97:
Page 98 and 99:
Page 100 and 101:
Page 102 and 103:
Page 104 and 105:
Page 106 and 107:
Page 108 and 109:
Page 110 and 111:
Page 112 and 113:
Page 114 and 115:
Page 116 and 117:
Page 118 and 119:
Page 120 and 121:
Page 122 and 123:
Page 124 and 125:
Page 126 and 127:
Page 128 and 129:
Page 130 and 131:
Page 132 and 133:
Page 134 and 135:
Page 136 and 137:
Page 138 and 139:
Page 140 and 141:
Page 142 and 143:
Page 144 and 145:
Page 146 and 147:
Page 148 and 149:
Page 150 and 151:
4 Using Direct Search 4-2 What Is D
Page 152 and 153:
4 Using Direct Search 4-4 Choose so
Page 154 and 155:
4 Using Direct Search 4-6 Optimize
Page 156 and 157:
4 Using Direct Search 4-8 The reaso
Page 158 and 159:
4 Using Direct Search 4-10 Pattern
Page 160 and 161:
4 Using Direct Search 4-12 The algo
Page 162 and 163:
4 Using Direct Search 4-14 The prob
Page 164 and 165:
4 Using Direct Search 4-16 Note By
Page 166 and 167:
4 Using Direct Search 4-18 8*[0 -1]
Page 168 and 169:
4 Using Direct Search 4-20 2 1.5 1
Page 170 and 171:
4 Using Direct Search 4-22 The dist
Page 172 and 173:
4 Using Direct Search 4-24 Update c
Page 174 and 175:
4 Using Direct Search 4-26 Search T
Page 176 and 177:
4 Using Direct Search 4-28 3 Set th
Page 178 and 179:
4 Using Direct Search 4-30 Referenc
Page 180 and 181:
4 Using Direct Search 4-32 Pattern
Page 182 and 183:
4 Using Direct Search 4-34 - Set Ae
Page 184 and 185:
4 Using Direct Search 4-36 The uppe
Page 186 and 187:
4 Using Direct Search 4-38 if optim
Page 188 and 189:
4 Using Direct Search 4-40 Now, whe
Page 190 and 191:
4 Using Direct Search 4-42 Custom P
Page 192 and 193:
4 Using Direct Search 4-44 x = -4.7
Page 194 and 195:
4 Using Direct Search 4-46 MaxFunEv
Page 196 and 197:
4 Using Direct Search 4-48 You can
Page 198 and 199:
4 Using Direct Search 4-50 [-100...
Page 200 and 201:
4 Using Direct Search 4-52 0 −5
Page 202 and 203:
4 Using Direct Search 4-54 mesh and
Page 204 and 205:
4 Using Direct Search 4-56 Example:
Page 206 and 207:
4 Using Direct Search 4-58 2 Choose
Page 208 and 209:
4 Using Direct Search 4-60 Algorith
Page 210 and 211:
4 Using Direct Search 4-62 The most
Page 212 and 213:
4 Using Direct Search 4-64 To see t
Page 214 and 215:
4 Using Direct Search 4-66 With the
Page 216 and 217:
4 Using Direct Search 4-68 3 Run th
Page 218 and 219:
4 Using Direct Search 4-70 The firs
Page 220 and 221:
4 Using Direct Search 4-72 When you
Page 222 and 223:
4 Using Direct Search 4-74 Note For
Page 224 and 225:
4 Using Direct Search 4-76 Iter f-c
Page 226 and 227:
4 Using Direct Search 4-78 3 Run th
Page 228 and 229:
4 Using Direct Search 4-80 This tim
Page 230 and 231:
4 Using Direct Search 4-82 The patt
Page 232 and 233:
4 Using Direct Search 4-84 Best Obj
Page 234 and 235:
4 Using Direct Search 4-86 If x0 is
Page 236 and 237:
4 Using Direct Search 4-88 The same
Page 238 and 239:
4 Using Direct Search 4-90 The init
Page 240 and 241:
4 Using Direct Search 4-92 ylabel('
Page 242 and 243:
4 Using Direct Search 4-94 distance
Page 244 and 245:
4 Using Direct Search 4-96 if nargi
Page 246 and 247:
4 Using Direct Search 4-98 You can
Page 248 and 249:
4 Using Direct Search 4-100 outpt =
Page 250 and 251:
5 Using the Genetic Algorithm 5-2 W
Page 252 and 253:
5 Using the Genetic Algorithm 5-4 U
Page 254 and 255:
5 Using the Genetic Algorithm 5-6 T
Page 256 and 257:
5 Using the Genetic Algorithm 5-8 G
Page 258 and 259:
5 Using the Genetic Algorithm 5-10
Page 260 and 261:
Page 262 and 263:
Page 264 and 265:
Page 266 and 267:
Page 268 and 269:
Page 270 and 271:
Page 272 and 273:
Page 274 and 275:
Page 276 and 277:
Page 278 and 279:
Page 280 and 281:
Page 282 and 283:
Page 284 and 285:
Page 286 and 287:
Page 288 and 289:
Page 290 and 291:
Page 292 and 293:
Page 294 and 295:
Page 296 and 297:
Page 298 and 299:
Page 300 and 301:
Page 302 and 303:
Page 304 and 305:
Page 306 and 307:
Page 308 and 309:
Page 310 and 311:
Page 312 and 313:
Page 314 and 315:
Page 316 and 317:
Page 318 and 319:
Page 320 and 321:
Page 322 and 323:
Page 324 and 325:
Page 326 and 327:
Page 328 and 329:
Page 330 and 331:
Page 332 and 333:
Page 334 and 335:
Page 336 and 337:
Page 338 and 339:
Page 340 and 341:
Page 342 and 343:
Page 344 and 345:
Page 346 and 347:
Page 348 and 349:
Page 350 and 351:
Page 352 and 353:
Page 354 and 355:
Page 356 and 357:
Page 358 and 359:
Page 360 and 361:
Page 362 and 363:
Page 364 and 365:
Page 366 and 367:
6 Using Simulated Annealing 6-2 Wha
Page 368 and 369:
6 Using Simulated Annealing 6-4 Usi
Page 370 and 371:
6 Using Simulated Annealing 6-6 To
Page 372 and 373:
6 Using Simulated Annealing 6-8 Man
Page 374 and 375:
6 Using Simulated Annealing 6-10 Si
Page 376 and 377:
6 Using Simulated Annealing 6-12 Ho
Page 378 and 379:
6 Using Simulated Annealing 6-14 T
Page 380 and 381:
6 Using Simulated Annealing 6-16 Us
Page 382 and 383:
6 Using Simulated Annealing 6-18 op
Page 384 and 385:
6 Using Simulated Annealing 6-20 x,
Page 386 and 387:
6 Using Simulated Annealing 6-22
Page 388 and 389:
7 Multiobjective Optimization 7-2 W
Page 390 and 391:
7 Multiobjective Optimization 7-4 F
Page 392 and 393:
7 Multiobjective Optimization 7-6 U
Page 394 and 395:
7 Multiobjective Optimization 7-8 3
Page 396 and 397:
7 Multiobjective Optimization 7-10
Page 398 and 399:
Page 400 and 401:
Page 402 and 403:
8 Parallel Processing 8-2 Backgroun
Page 404 and 405:
8 Parallel Processing 8-4 Suppose,
Page 406 and 407:
8 Parallel Processing 8-6 reaches a
Page 408 and 409:
8 Parallel Processing 8-8 Implement
Page 410 and 411:
8 Parallel Processing 8-10 Run gamu
Page 412 and 413:
8 Parallel Processing 8-12 MultiSta
Page 414 and 415:
8 Parallel Processing 8-14 After yo
Page 416 and 417:
8 Parallel Processing 8-16 Parallel
Page 418 and 419:
8 Parallel Processing 8-18
Page 420 and 421:
9 Options Reference 9-2 GlobalSearc
Page 422 and 423:
9 Options Reference 9-4 run when th
Page 424 and 425:
9 Options Reference 9-6 If you spec
Page 426 and 427:
9 Options Reference 9-8 If MaxWaitC
Page 428 and 429:
9 Options Reference 9-10 In this se
Page 430 and 431:
9 Options Reference 9-12 - TolX —
Page 432 and 433:
9 Options Reference 9-14 the number
Page 434 and 435:
9 Options Reference 9-16 Note If yo
Page 436 and 437:
9 Options Reference 9-18 The search
Page 438 and 439:
9 Options Reference 9-20 Off or On
Page 440 and 441:
9 Options Reference 9-22 Specify
Page 442 and 443:
9 Options Reference 9-24 - TolFun
Page 444 and 445:
9 Options Reference 9-26 When Evalu
Page 446 and 447:
9 Options Reference 9-28 Option Ava
Page 448 and 449:
9 Options Reference 9-30 Option Ava
Page 450 and 451:
9 Options Reference 9-32 See “Set
Page 452 and 453:
9 Options Reference 9-34 To display
Page 454 and 455:
9 Options Reference 9-36 Selection
Page 456 and 457:
9 Options Reference 9-38 The functi
Page 458 and 459:
9 Options Reference 9-40 - Set Scal
Page 460 and 461:
9 Options Reference 9-42 The input
Page 462 and 463:
9 Options Reference 9-44 options =
Page 464 and 465:
9 Options Reference 9-46 - Selects
Page 466 and 467:
9 Options Reference 9-48 Your cross
Page 468 and 469:
9 Options Reference 9-50 space (gen
Page 470 and 471:
9 Options Reference 9-52 Enter @myf
Page 472 and 473:
9 Options Reference 9-54 Max Constr
Page 474 and 475:
9 Options Reference 9-56 Simulated
Page 476 and 477:
9 Options Reference 9-58 optimvalue
Page 478 and 479:
9 Options Reference 9-60 - @anneali
Page 480 and 481:
9 Options Reference 9-62 Stopping C
Page 482 and 483:
9 Options Reference 9-64 - 'iter'
Page 484 and 485:
9 Options Reference 9-66
Page 486 and 487:
10 Function Reference 10-2 GlobalSe
Page 488 and 489:
10 Function Reference 10-4 Genetic
Page 490 and 491:
10 Function Reference 10-6 Simulate
Page 492 and 493:
11 Class Reference 11-2
Page 494 and 495:
createOptimProblem 12-2 Purpose Cre
Page 496 and 497:
createOptimProblem 12-4 Output Argu
Page 498 and 499:
CustomStartPointSet 12-6 Get the fo
Page 500 and 501:
ga 12-8 x = ga(fitnessfcn,nvars,A,b
Page 502 and 503:
ga 12-10 If the problem has m linea
Page 504 and 505:
ga 12-12 where constraintfile.m is
Page 506 and 507:
ga 12-14 Exit Flag Meaning 1 Withou
Page 508 and 509:
ga 12-16 Examples Given the followi
Page 510 and 511:
gamultiobj 12-18 Purpose Find minim
Page 512 and 513:
gamultiobj 12-20 rngstate Optional
Page 514 and 515:
gamultiobj 12-22 end y(i,1) = x(i)
Page 516 and 517:
gamultiobj 12-24 See Also ga | gaop
Page 518 and 519:
gaoptimset 12-26 Purpose Create gen
Page 520 and 521:
gaoptimset 12-28 Option Description
Page 522 and 523:
Page 524 and 525:
Page 526 and 527:
GlobalOptimSolution 12-34 Copy Sema
Page 528 and 529:
GlobalSearch 12-36 'off' —Nodispl
Page 530 and 531:
GlobalSearch 12-38 Default: [] Star
Page 532 and 533:
CustomStartPointSet.list 12-40 Purp
Page 534 and 535:
RandomStartPointSet.list 12-42 Algo
Page 536 and 537:
MultiStart 12-44 OutputFcns A funct
Page 538 and 539:
MultiStart 12-46 Methods Copy Seman
Page 540 and 541:
patternsearch 12-48 Ax ≤ b Aeq
Page 542 and 543:
patternsearch 12-50 Exit Flag 1 Mea
Page 544 and 545:
patternsearch 12-52 x = 0.6667 1.33
Page 546 and 547:
psoptimget 12-54 Purpose Obtain val
Page 548 and 549:
psoptimset 12-56 Option Description
Page 550 and 551:
psoptimset 12-58 Option Description
Page 552 and 553:
GlobalSearch.run 12-60 Purpose Find
Page 554 and 555:
GlobalSearch.run 12-62 funcCount Nu
Page 556 and 557:
MultiStart.run 12-64 Purpose Run lo
Page 558 and 559:
MultiStart.run 12-66 output 2 At le
Page 560 and 561:
RandomStartPointSet 12-68 Purpose R
Page 562 and 563:
saoptimget 12-70 Purpose Values of
Page 564 and 565:
saoptimset 12-72 AnnealingFcn: @ann
Page 566 and 567:
saoptimset 12-74 Option Description
Page 568 and 569:
simulannealbnd 12-76 solver 'simula
Page 570 and 571:
simulannealbnd 12-78 x = 0.0392 -31
Page 572 and 573:
simulannealbnd 12-80 See Also ga |
Page 574 and 575:
A Examples A-2 GlobalSearch and Mul
Page 576 and 577:
A Examples A-4 Genetic Algorithm
Page 578 and 579:
A Examples A-6
Page 580 and 581:
Index global 5-97 local 5-97 minimi
show all

Global Optimization Toolbox User's Guide - MathWorks

Create successful ePaper yourself

Delete template?

Save as template?