Evolution and Optimum Seeking

More documents

Recommendations

Info

( + ) <strong>Evolution</strong> Strategy KORR 397 C 19 C K2=L1+IELTER*GLEICH(D) CALL GNPOOL 1(1,L1,K1,K2,NZ,N,IELTER,IREKOS,NS,NY,S,Y,GLEICH) C STEP SIZES SUPPLIED FOR THE DESCENDANT FROM THE C C C POOL OF GENES. IF(BKORRL) CALL GNPOOL 1(2,L1,K1,K2,NZ,N+NS,IELTER,IREKOP,NP,NY,P,Y,GLEICH) C POSITIONAL ANGLES OF ELLIPSOID SUPPLIED FOR THE C DESCENDANT FROM THE POOL OF GENES WHEN CORRELATION C C IS REQUIRED. CALL MUTATI 1(NL,NM,BKORRL,DELTAS,DELTAI,DELTAP,N,NS,NP,X,S,P, 2GAUSSN,GLEICH) C C CALL TO MUTATION SUBROUTINE FOR ALL VARIABLES, C INCLUDING POSSIBLY COORDINATE TRANSFORMATION. S C (AND P) ARE ALREADY THE NEW ATTRIBUTES OF THE C DESCENDANT, WHILE X REPRESENTS THE CHANGES TO BE C C C MADE IN THE OBJECT VARIABLES. CALL GNPOOL 1(3,L1,K1,K2,NZ,0,IELTER,IREKOX,N,NY,X,Y,GLEICH) C OBJECT VARIABLES SUPPLIED FOR THE DESCENDANT FROM C THE POOL OF GENES AND ADDITION OF THE MODIFICATION C VECTOR. X NOW REPRESENTS THE NEW STATE OF THE C C DESCENDANT. LMUTAT=LMUTAT+1 IF(IFALLK.GT.0) GOTO 20 C C EVALUATION OF THE AUXILIARY OBJECTIVE FUNCTION FOR C C THE SEARCH FOR A FEASIBLE VECTOR. Z=ZULASS(N,M,X,RESTRI) IF(Z)40,40,22 20 C IF(M.EQ.0) GOTO 21 C CHECK FEASIBILITY OF DESCENDANT. IF THE RESULT IS
398 Appendix B C NEGATIVE (LETHAL MUTATION), THE MUTATION IS NOT C COUNTED AS REGARDS THE NACHKO PARAMETER. C IF(.NOT.BLETAL(N,M,X,RESTRI)) GOTO 21 IF(.NOT.BKOMMA) GOTO 25 LMUTAT=LMUTAT-1 L3=L3+1 IF(L3.LT.NACHKO) GOTO 18 L3=0 C C TIME CHECK MADE NOT ONLY AFTER EACH GENERATION BUT C ALSO AFTER EVERY NACHKO LETHAL MUTATIONS FOR C CERTAINTY. C IF(TKONTR(D).LT.TMAXIM) GOTO 18 IFALLK=3 GOTO 26 21 Z=ZIELFU(N,X) C C EVALUATION OF OBJECTIVE FUNCTION VALUE FOR THE C DESCENDANT. C 22 IF(BKOMMA.AND.LMUTAT.LE.IELTER) GOTO 23 IF(Z-ZSCHL)24,24,25 23 LSCHL=L2+LMUTAT-1 24 CALL SPEICH 1(LSCHL*NZ,BKORRL,EPSILO,N,NS,NP,NY,Z,X,S,P,Y) C C TRANSFER OF DATA OF DESCENDANT TO PART OF ARRAY Y C HOLDING THE PARENTS FOR THE NEXT GENERATION. C IF(.NOT.BKOMMA.OR.LMUTAT.GE.IELTER) CALL MINMAX 1(-1.,L2,NZ,ZSCHL,LSCHL,IELTER,NY,Y) C C LOOK FOR THE CURRENTLY WORST INDIVIDUAL STORED IN C ARRAY Y WITHOUT CONSIDERING THE PARENTS THAT STILL C CAN PRODUCE DESCENDANTS IN THIS GENERATION. C 25 IF(LMUTAT.LT.NACHKO) GOTO 18 C C END OF GENERATION. C 26 CALL MINMAX 1(1.,L2,NZ,ZBEST,LBEST,IELTER,NY,Y)
Page 1:
Evolution and Optimum Seeking Hans-
Page 4 and 5:
vi Multiple Data) machines with man
Page 6 and 7:
viii 3.2.1.6 Complex Strategy of Bo
Page 9 and 10:
Chapter 1 Introduction There is sca
Page 11 and 12:
Introduction 3 simple matter to col
Page 13 and 14:
Chapter 2 Problems and Methods of O
Page 15 and 16:
Particular Problems and Methods of
Page 17 and 18:
Page 19 and 20:
Page 21 and 22:
Page 23 and 24:
Page 25 and 26:
Page 27 and 28:
Other Special Cases 19 with expecta
Page 29 and 30:
Other Special Cases 21 parts of the
Page 31 and 32:
Chapter 3 Hill climbing Strategies
Page 33 and 34:
One Dimensional Strategies 25 then
Page 35 and 36:
One Dimensional Strategies 27 Even
Page 37 and 38:
One Dimensional Strategies 29 The b
Page 39 and 40:
One Dimensional Strategies 31 F(x)
Page 41 and 42:
One Dimensional Strategies 33 For t
Page 43 and 44:
One Dimensional Strategies 35 It is
Page 45 and 46:
One Dimensional Strategies 37 F P F
Page 47 and 48:
Multidimensional Strategies 39 the
Page 49 and 50:
Multidimensional Strategies 41 asch
Page 51 and 52:
Multidimensional Strategies 43 e 2
Page 53 and 54:
Multidimensional Strategies 45 Step
Page 55 and 56:
Multidimensional Strategies 47 Numb
Page 57 and 58:
Multidimensional Strategies 49 wher
Page 59 and 60:
Page 61 and 62:
Multidimensional Strategies 53 Numb
Page 63 and 64:
Multidimensional Strategies 55 The
Page 65 and 66:
Multidimensional Strategies 57 Anum
Page 67 and 68:
Page 69 and 70:
Multidimensional Strategies 61 Iter
Page 71 and 72:
Multidimensional Strategies 63 (If
Page 73 and 74:
Multidimensional Strategies 65 eval
Page 75 and 76:
Multidimensional Strategies 67 The
Page 77 and 78:
Multidimensional Strategies 69 devi
Page 79 and 80:
Multidimensional Strategies 71 spec
Page 81 and 82:
Multidimensional Strategies 73 othe
Page 83 and 84:
Multidimensional Strategies 75 anot
Page 85 and 86:
Multidimensional Strategies 77 3.2.
Page 87 and 88:
Page 89 and 90:
Multidimensional Strategies 81 Brow
Page 91 and 92:
Multidimensional Strategies 83 (197
Page 93 and 94:
Multidimensional Strategies 85 meth
Page 95 and 96:
Chapter 4 Random Strategies One gro
Page 97 and 98:
Random Strategies 89 parts is taken
Page 99 and 100:
Random Strategies 91 Pardalos and R
Page 101 and 102:
Random Strategies 93 to write the n
Page 103 and 104:
Random Strategies 95 the expectatio
Page 105 and 106:
Random Strategies 97 maintained at
Page 107 and 108:
Random Strategies 99 works entirely
Page 109 and 110:
Random Strategies 101 the principle
Page 111 and 112:
Random Strategies 103 out, a limite
Page 113 and 114:
Chapter 5 Evolution Strategies for
Page 115 and 116:
The Two Membered Evolution Strategy
Page 117 and 118:
Page 119 and 120:
Page 121 and 122:
Page 123 and 124:
Page 125 and 126:
Page 127 and 128:
A Multimembered Evolution Strategy
Page 129 and 130:
Page 131 and 132:
Page 133 and 134:
Page 135 and 136:
Page 137 and 138:
Page 139 and 140:
Page 141 and 142:
Page 143 and 144:
Page 145 and 146:
Page 147 and 148:
Page 149 and 150:
Page 151 and 152:
Page 153 and 154:
Page 155 and 156:
Page 157 and 158:
Page 159 and 160:
Genetic Algorithms 151 too is the c
Page 161 and 162:
Genetic Algorithms 153 mean objecti
Page 163 and 164:
Genetic Algorithms 155 p( ∆x) 1 1
Page 165 and 166:
Genetic Algorithms 157 out any chan
Page 167 and 168:
Genetic Algorithms 159 Average Numb
Page 169 and 170:
Simulated Annealing 161 There are t
Page 171 and 172:
Tabu Search and Other Hybrid Concep
Page 173 and 174:
Chapter 6 Comparison of Direct Sear
Page 175 and 176:
Theoretical Results 167 Oettli, 196
Page 177 and 178:
Theoretical Results 169 where 0
Page 179 and 180:
Theoretical Results 171 tions. Simi
Page 181 and 182:
Numerical Comparison of Strategies
Page 183 and 184:
Page 185 and 186:
Page 187 and 188:
Page 189 and 190:
Page 191 and 192:
Page 193 and 194:
Page 195 and 196:
Page 197 and 198:
Page 199 and 200:
Page 201 and 202:
Page 203 and 204:
Page 205 and 206:
Page 207 and 208:
Page 209 and 210:
Page 211 and 212:
Page 213 and 214:
Page 215 and 216:
Page 217 and 218:
Page 219 and 220:
Page 221 and 222:
Page 223 and 224:
Page 225 and 226:
Page 227 and 228:
Page 229 and 230:
Page 231 and 232:
Page 233 and 234:
Page 235 and 236:
Page 237 and 238:
Page 239 and 240:
Page 241 and 242:
Core storage required 233 term \cor
Page 243 and 244:
Chapter 7 Summary and Outlook So, i
Page 245 and 246:
Summary and Outlook 237 numerical o
Page 247 and 248:
Summary and Outlook 239 considerabl
Page 249 and 250:
Summary and Outlook 241 is called t
Page 251 and 252:
Summary and Outlook 243 to the prod
Page 253 and 254:
Summary and Outlook 245 tition betw
Page 255 and 256:
Summary and Outlook 247 the experim
Page 257 and 258:
Chapter 8 References Glossary of ab
Page 259 and 260:
References 251 Anscombe, F.J. (1959
Page 261 and 262:
References 253 Bandler, J.W. (1969b
Page 263 and 264:
References 255 Bendin, F. (1992), E
Page 265 and 266:
References 257 Booth, A.D. (1955),
Page 267 and 268:
References 259 Brent, R.P. (1971),
Page 269 and 270:
References 261 Carroll, C.W. (1961)
Page 271 and 272:
References 263 Courant, R., D. Hilb
Page 273 and 274:
References 265 Davies, M., I.J. Whi
Page 275 and 276:
References 267 Dvoretzky, A. (1956)
Page 277 and 278:
References 269 Fiacco, A.V. (1974),
Page 279 and 280:
References 271 Fogel, L.J., A.J. Ow
Page 281 and 282:
References 273 Gill, P.E., W. Murra
Page 283 and 284:
References 275 Graves, R.L., P. Wol
Page 285 and 286:
References 277 Heckler, R., H.-P. S
Page 287 and 288:
References 279 Ho meister, F., H.-P
Page 289 and 290:
References 281 Idelsohn, J.M. (1964
Page 291 and 292:
References 283 Karnopp, D.C. (1966)
Page 293 and 294:
References 285 Kochen, M., H.M. Has
Page 295 and 296:
References 287 Kunzi, H.P., H.G. Tz
Page 297 and 298:
References 289 LeCam, L.M., J. Neym
Page 299 and 300:
References 291 Mamen, R., D.Q. Mayn
Page 301 and 302:
294 References Miele, A., H.Y. Huan
Page 303 and 304:
296 References Murray, W. (Ed.) (19
Page 305 and 306:
298 References Oldenburger, R. (Ed.
Page 307 and 308:
300 References Peschel, M. (1980),
Page 309 and 310:
302 References Powell, M.J.D. (1970
Page 311 and 312:
304 References Rechenberg, I. (1989
Page 313 and 314:
306 References Rybashov, M.V. (1969
Page 315 and 316:
308 References Schmidt, J.W., K. Ve
Page 317 and 318:
310 References Shedler, G.S. (1967)
Page 319 and 320:
312 References Steinbuch, K. (1971)
Page 321 and 322:
314 References Tabak, D. (1970), Ap
Page 323 and 324:
316 References Varela, F.J., P. Bou
Page 325 and 326:
318 References White, L.J., R.G. Da
Page 327 and 328:
320 References Youden, W.J., O. Kem
Page 329 and 330:
322 References Glossary of Abbrevia
Page 331 and 332:
324 References
Page 333 and 334:
326 Appendix A Problem 1.2 Objectiv
Page 335 and 336:
328 Appendix A Minimum: x =(3 0:5)
Page 337 and 338:
330 Appendix A Figure A.3: Graphica
Page 339 and 340:
332 Appendix A Several of the searc
Page 341 and 342:
Page 343 and 344:
Page 345 and 346:
338 Appendix A Minimum: Start: Prob
Page 347 and 348:
340 Appendix A Problem 2.20 Objecti
Page 349 and 350:
342 Appendix A Problem 2.23 Objecti
Page 351 and 352:
344 Appendix A Start: x (0) i =10 f
Page 353 and 354: 346 Appendix A on the interval 0 y
Page 355 and 356: 348 Appendix A Problem 2.32 after B
Page 357 and 358: 350 Appendix A Constraints: Gj(x) =
Page 359 and 360: 352 Appendix A The constraints form
Page 361 and 362: 354 Appendix A Start: x (0) =(250 2
Page 363 and 364: 356 Appendix A Problem 2.44 As Prob
Page 365 and 366: 358 Appendix A Figure A.29: Graphic
Page 367 and 368: 360 Appendix A Start: Figure A.31:
Page 369 and 370: 362 Appendix A Problem 3.2 (analogo
Page 371 and 372: 364 Appendix A Problem 3.6 (analogo
Page 373 and 374: 366 Appendix A Minimum: x i =0 for
Page 375 and 376: 368 Appendix B LF (integer) Return
Page 377 and 378: 370 Appendix B 4. Convergence crite
Page 379 and 380: 372 Appendix B 8. Function Z(S,R) T
Page 381 and 382: 374 Appendix B 25 L(K)=L(K+1) L(10)
Page 383 and 384: 376 Appendix B LF=2 (continued) No
Page 385 and 386: 378 Appendix B man), vol. 15 of Pro
Page 387 and 388: 380 Appendix B instead of T, as a p
Page 389 and 390: 382 Appendix B 15 CONTINUE 16 FF=F(
Page 391 and 392: 384 Appendix B SK(KS)=AMAX1(SM(I),A
Page 393 and 394: 386 Appendix B B.3 ( + ) Evolution
Page 395 and 396: 388 Appendix B EPSILO (one dimensio
Page 397 and 398: 390 Appendix B GLEICH (real functio
Page 399 and 400: 392 Appendix B GLEICH, and TKONTR d
Page 401 and 402: 394 Appendix B 1 NL=1+N-NS NM=N-1 N
Page 403: 396 Appendix B ZSTERN=ZBEST K=LBEST
Page 407 and 408: 400 Appendix B C C PREPARE FINAL DA
Page 409 and 410: 402 Appendix B 2 IF(.NOT.BKOMMA.OR.
Page 411 and 412: 404 Appendix B 32 WRITE(KANAL,126)
Page 413 and 414: 406 Appendix B DO 4 I=1,NX KI=KI1 I
Page 415 and 416: 408 Appendix B Subroutine MINMAX MI
Page 417 and 418: 410 Appendix B 2 IF(U.LT..965487131
Page 419 and 420: 412 Appendix B parameters by multip
Page 421 and 422: 414 Appendix B
Page 423 and 424: 416 Appendix C - SIMP Simplex strat
Page 425 and 426: 418 Appendix C C.3.2 How to Install
Page 427 and 428: 420 Appendix C { } return(0.26*(x[0
Page 429 and 430: 422 Appendix C 1 No recombination 2
Page 431 and 432: 424 Appendix C 8e-07 8e-07 Initial
Page 433 and 434: 426 Index Banach, S., 10 Bandler, J
Page 435 and 436: 428 Index Coordinate strategy, 41{4
Page 437 and 438: 430 Index Evolution strategy, 3, 6,
Page 439 and 440: 432 Index Graves, R.L., 23 Great de
Page 441 and 442: 434 Index Khurgin, Ya.I., 89 Kiefer
Page 443 and 444: 436 Index Michie, D., 102 Mickey, M
Page 445 and 446: 438 Index Parkinson, J.M., 61 Parta
Page 447 and 448: 440 Index Rotating coordinates meth
Page 449 and 450: 442 Index Storey, C., 23, 50, 54 St
Page 451: 444 Index Wilson, S.W., 103 Witt, U
show all

Evolution and Optimum Seeking

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?