New optimization techniques in engineering:
Gespeichert in:
Format: | Buch |
---|---|
Sprache: | English |
Veröffentlicht: |
Berlin [u.a.]
Springer
2004
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Schriftenreihe: | Studies in fuzziness and soft computing
141 |
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | Literaturangaben |
Beschreibung: | XXII, 712 S. graph. Darst. : 24 cm |
ISBN: | 354020167X |
Internformat
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245 | 1 | 0 | |a New optimization techniques in engineering |c Godfrey C. Onwubolu ; B. V. Babu |
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GODFREY C. ONWUBOLU B.V.BABU NEW OPTIMIZATION TECHNIQUES IN ENGINEERING
SPRINGER CONTENTS CHAPTER 1: INTRODUCTION 1 GODFREY C ONWUBOLU AND B V
BABU 1.1 OPTIMIZATION 1 1.2 STOCHASTIC OPTIMIZATION TECHNIQUE 4 1.2.1
LOCAL SEARCH 4 1.2.2 POPULATION-BASED SEARCH 5 1.3 FRAMEWORK FOR
WELL-ESTABLISHED OPTIMIZATION TECHNIQUES 6 1.4 NEW & NOVEL OPTIMIZATION
TECHNIQUES 7 1.5 THE STRUCTURE OF THE BOOK 9 1.6 SUMMARY 10 REFERENCES
11 PART I: NEW OPTIMIZATION TECHNIQUES CHAPTER 2: INTRODUCTION TO
GENETIC ALGORITHMS FOR ENGINEERING OPTIMIZATION KALYANMOY DEB 13 2.1
INTRODUCTION 13 2.2 CLASSICAL SEARCH AND OPTIMIZATION TECHNIQUES 14 2.3
MOTIVATION FROM NATURE 16 2.4 GENETIC ALGORITHMS 17 2.4.1 WORKING
PRINCIPLE 17 2.4.2 AN ILLUSTRATION 22 2.4.3 A HAND CALCULATION 27 2.4.4
CONSTRAINT HANDLING 31 2.5 CAR SUSPENSION DESIGN USING GENETIC
ALGORITHMS 34 2.5.1 TWO-DIMENSIONAL MODEL 34 2.5.2 THREE-DIMENSIONAL
MODEL 37 2.6 REAL-PARAMETER GENETIC ALGORITHMS 40 2.7 A COMBINED GENETIC
ALGORITHM 43 2.7.1 GEAR TRAIN DESIGN 44 2.8 A SPRING DESIGN 45 2.9
ADVANCED GENETIC ALGORITHMS 47 2.10 CONCLUSIONS 48 REFERENCES 49 XII
CONTENTS CHAPTER 3: MEMETIC ALGORITHMS 53 PABLO MOSCATO, CARLOS COTTA
AND ALEXANDRE MENDES 3.1 3.2 3.3 3.4 3.4.1 3.4.2 3.4.3 3.4.4 3.4.5 3.4.6
3.4.7 3.5 INTRODUCTION THE MA SEARCH TEMPLATE DESIGN OF EFFECTIVE MAS
APPLICATIONS OF MAS NP-HARD COMBINATORIAL OPTIMIZATION PROBLEMS
TELECOMUNICATIONS AND NETWORKING SCHEDULING AND TIMETABLING PROBLEMS
MACHINE LEARNING AND ROBOTICS ENGINEERING, ELECTRONICS AND
ELECTROMAGNETICS PROBLEMS INVOLVING OPTIMIZATION IN MOLECULES OTHER
APPLICATIONS CONCLUSIONS AND FUTURE DIRECTIONS REFERENCES CHAPTER 4:
SCATTER SEARCH AND PATH RELINKING: FOUNDATIONS AND ADVANCED DESIGNS FRED
GLOVER, MANUEL LAGUNA AND RAFAEL MARTI 4.1 4.2 4.2.1 4.2.2 4.3 4.3.1
4.3.2 INTRODUCTION FOUNDATIONS SCATTER SEARCH PATH RELINKING ADVANCED
STRATEGIES SCATTER SEARCH PATH RELINKING REFERENCES CHAPTER 5: ANT
COLONY OPTIMIZATION VITTORIO MANIEZZO, LUCA MARIA GAMBARDELLA, FABIO DE
LUIGI 5.1 5.2 5.2.1 5.2.2 5.2.3 5.3 5.3.1 5.3.2 5.3.3 5.3.4 5.4 5.5
INTRODUCTION ANT COLONY OPTIMIZATION ANT SYSTEM ANT COLONY SYSTEM ANTS
SIGNIFICANT PROBLEMS SEQUENTIAL ORDERING PROBLEM VEHICLE ROUTING
PROBLEMS QUADRATIC ASSIGNMENT PROBLEM OTHER PROBLEMS CONVERGENCE PROOFS
CONCLUSIONS REFERENCES 53 54 60 65 66 66 67 67 68 68 69 69 72 87 87 89
89 91 93 93 96 99 101 101 102 103 105 107 109 110 . ILL 113 114 115 116
117 CONTENTS XIII CHAPTER 6: DIFFERENTIAL EVOLUTION 123 JOUNI LAMPINEN
AND RAINER STORN 6.1 6.2 6.3 6.3.1 6.3.2 6.3.3 6.3.4 6.4 6.4.1 6.4.2 6.4
6.5.1 6.5.2 6.6 6.6.1 6.6.2 6.6.3 6.7 6.8 INTRODUCTION MIXED
INTEGER-DISCRETE-CONTINUOUS NON-LINEAR PROGRAMMING DIFFERENTIAL
EVOLUTION INITIALIZATION MUTATION AND CROSSOVER SELECTION DE DYNAMICS
CONSTRAINT HANDLING BOUNDARY CONSTRAINTS CONSTRAINT FUNCTIONS HANDLING
INTEGER AND DISCRETE VARIABLES METHODS AN ILLUSTRATIVE EXAMPLE NUMERICAL
EXAMPLES EXAMPLE 1: DESIGNING A GEAR TRAIN EXAMPLE 2: DESIGNING A
PRESSURE VESSEL EXAMPLE 3: DESIGNING A COIL COMPRESSION SPRING DE'S
SENSITIVITY TO ITS CONTROL VARIABLES CONCLUSIONS REFERENCES CHAPTER 7:
SOMA - SELF-ORGANIZING MIGRATING ALGORITHM IVAN ZELINKA 7.1 7.2 7.3 7.4
7.5 7.6 7.7 7.8 7.9 7.10 7.11 7.11.1 7.11.2 7.11.3 7.12 7.13 7.14 7.15
INTRODUCTION FUNCTION DOMAIN OF SOMA POPULATION MUTATION CROSSOVER
PARAMETERS AND TERMINOLOGY PRINCIPLES OF SOMA VARIATIONS OF SOMA SOMA
DEPENDENCE ON CONTROL PARAMETERS ON THE SOMA CLASSIFICATION AND SOME
ADDITIONAL INFORMATION CONSTRAINT HANDLING BOUNDARY CONSTRAINTS
CONSTRAINT FUNCTIONS HANDLING OF INTEGER AND DISCRETE VARIABLES SELECTED
APPLICATIONS AND OPEN PROJECTS GALLERY OF TEST FUNCTIONS SOMA ON TESTED
FUNCTIONS CONCLUSION REFERENCES 123 124 125 127 128 130 132 138 138 139
142 142 143 144 146 149 153 157 160 163 167 167 168 169 170 171 . 172
175 179 180 182 184 185 186 187 189 192 200 212 215 XIV CONTENTS
CHAPTER 8: DISCRETE PARTICLE SWARM OPTIMIZATION, ILLUSTRATED BY THE
TRAVELING SALESMAN PROBLEM 219 MAURICE CLERC 8.1 INTRODUCTION 219 8.2 A
FEW WORDS ABOUT "CLASSICAL" PSO 219 8.3 DISCRETE PSO 221 8.4 PSO
ELEMENTS FOR TSP 222 8.4.1 POSITIONS AND STATE SPACE 222 8.4.2 OBJECTIVE
FUNCTION 222 8.4.3 VELOCITY 223 8.4.4 OPPOSITE OF A VELOCITY 223 8.4.5
MOVE (ADDITION) "POSITION PLUS VELOCITY" 223 8.4.6 SUBTRACTION "POSITION
MINUS POSITION" 224 8.4.7 ADDITION "VELOCITY PLUS VELOCITY" 224 8.4.8
MULTIPLICATION "COEFFICIENT TIMES VELOCITY" 224 8.4.9 DISTANCE BETWEEN
TWO POSITIONS 225 8.5 THE ALGORITHM "PSO FOR TSP". CORE AND VARIATIONS
225 8.5.1 EQUATIONS 225 8.5.2 NOHOPE TESTS 226 8.5.3 REHOPE PROCESS 227
8.5.4 ADAPTIVE REHOPE METHOD (ARM) 228 8.5.5 QUEENS 228 8.5.6 EXTRA-BEST
PARTICLE 228 8.5.7 PARALLEL AND SEQUENTIAL VERSIONS 229 8.6 EXAMPLES AND
RESULTS 229 8.6.1 PARAMETERS CHOICE 229 8.6.2 A TOY EXAMPLE AS
ILLUSTRATION 230 8.6.3 SOME RESULTS, AND DISCUSSION 235 APPENDIX 236
REFERENCES 238 PART II: APPLICATIONS OF NEW OPTIMIZATION TECHNIQUES IN
ENGINEERING PART II. 1: CHEMICAL/METALLURGICAL ENGINEERING CHAPTER 9:
APPLICATIONS IN HEAT TRANSFER 241 B V BABU 9.1 INTRODUCTION . 241 9.2
HEAT TRANSFER PARAMETERS IN TRICKLE BED REACTOR 244 9.2.1 ORTHOGONAL
COLLOCATION 247 9.2.2 EXPERIMENTAL SETUP AND PROCEDURE 249 9.2.3 RESULTS
AND DISCUSSIONS 251 9.2.4 CONCLUSIONS 258 CONTENTS XV 9.3 DESIGN OF
SHELL-AND-TUBE HEAT EXCHANGER 259 9.3.1 THE OPTIMAL HED PROBLEM 259
9.3.2 PROBLEM FORMULATION 262 9.3.3 RESULTS & DISCUSSIONS 263 9.3.4
CONCLUSIONS 276 NOMENCLATURE 277 REFERENCES 281 CHAPTER 10: APPLICATIONS
IN MASS TRANSFER 287 B V BABU 10.1 INTRODUCTION 10.2 OPTIMIZATION OF
LIQUID EXTRACTION PROCESS 10.2.1 PROCESS MODEL 10.2.2 OBJECTIVE FUNCTION
10.2.3 INEQUALITY CONSTRAINTS 10.2.4 RESULTS & DISCUSSION 10.2.5
CONCLUSIONS 10.3 OPTIMIZATION OF A SEPARATION TRAIN OF DISTILLATION
COLUMNS 10.3.1 PROBLEM FORMULATION 10.3.2 RESULTS & DISCUSSION 10.3.3
CONCLUSIONS 10.4 OPTIMIZATION AND SYNTHESIS OF HEAT INTEGRATED
DISTILLATION COLUMN SEQUENCES 10.4.1 PROBLEM FORMULATION 10.4.2
SYNTHESIS OF DISTILLATION SYSTEM 10.4.3 RESULTS & DISCUSSION 10.4.4
CONCLUSIONS REFERENCES 287 287 290 291 291 292 294 295 295 298 300 300
301 303 305 308 309 CHAPTER 11: APPLICATIONS IN FLUID MECHANICS 313 B V
BABU 11.1 INTRODUCTION 313 11.2 GAS TRANSMISSION NETWORK 314 11.2.1
PROBLEM FORMULATION 315 11.2.2 RESULTS & DISCUSSION 320 11.3 WATER
PUMPING SYSTEM 327 11.3.1 DIFFERENTIAL EVOLUTION STRATEGIES 327 11.3.2
PROBLEM FORMULATION 331 11.3.3 RESULTS & DISCUSSION 332 11.4 CONCLUSIONS
334 REFERENCES 336 CHAPTER 12: APPLICATIONS IN REACTION ENGINEERING 341
B V BABU 12.1 INTRODUCTION 341 XVI CONTENTS 12.2 DESIGN OF AUTO-THERMAL
AMMONIA SYNTHESIS REACTOR 12.2.1 AMMONIA SYNTHESIS REACTOR 12.2.2
PROBLEM FORMULATION 12.2.3 SIMULATED RESULTS & DISCUSSION 12.2.4
OPTIMIZATION 12.2.5 CONCLUSIONS 12.3 THERMAL CRACKING OPERATION 12.3.1
THERMAL CRACKING 12.3.2 PROBLEM DESCRIPTION 12.3.3 PROBLEM REFORMULATION
12.3.4 SIMULATED RESULTS AND DISCUSSION 12.3.5 CONCLUSIONS REFERENCES
343 343 345 345 352 356 356 R 357 357 360 361 362 363 PART II.2:
CIVIL/ENVIRONMENTAL ENGINEERING/ INTERDISCIPLINARY CHAPTER 13: NEW IDEAS
AND APPLICATIONS OF SCATTER SEARCH AND PATH RELINKING 367 FRED GLOVER,
MANUEL LAGUNA AND RAFAEL MARTI 13.1 INTRODUCTION 367 13.2 SCATTER SEARCH
APPLICATIONS 368 13.2.1 NEURAL NETWORK TRAINING 368 13.2.2
MULTI-OBJECTIVE ROUTING PROBLEM 369 13.2.3 OPTQUEST: A COMMERCIAL
IMPLEMENTATION 371 13.2.4 A CONTEXT-INDEPENDENT METHOD FOR PERMUTATION
PROBLEMS 373 13.2.5 CLASSICAL VEHICLE ROUTING 375 13.3 PATH RELINKING
APPLICATIONS 378 13.3.1 MATRIX BANDWIDTH MINIMIZATION 378 13.3.2 ARC
CROSSING MINIMIZATION 379 REFERENCES 382 CHAPTER 14: IMPROVEMENT OF
SEARCH PROCESS IN GENETIC ALGORITHMS: AN APPLICATION OF PCB ASSEMBLY
SEQUENCING PROBLEM * 385 NGUYEN VAN HOP AND MARIO T TABUCANON 14.1 14.2
14.2.1 14.2.2 14.2.3 14.2.4 14.2.5 14.3 14.3.1 14.3.2 INTRODUCTION
GUIDED GENETIC ALGORITHM (GGA) CODING SCHEME FITNESS FUNCTION GENETIC
OPERATORS INPUT PARAMETERS GUIDED GENETIC ALGORITHM (GGA) THE GGA FOR
THE PCB ASSEMBLY SEQUENCING PROBLEM THE PCB SEQUENCING PROBLEM ON
MULTIPLE NON-IDENTICAL PARALLEL MACHINES RELATED WORKS 385 388 389 . 390
390 394 395 396 396 399 CONTENTS XVII 14.3.3 THE GGA SOLUTION 401 14.3.4
EXPERIMENTAL RESULTS 403 14.4 CONCLUDING REMARKS 407 REFERENCES 408
CHAPTER 15: AN ANTS HEURISTIC FOR THE LONG-TERM CAR POOLING PROBLEM: ACO
411 VITTORIO MANIEZZO, ANTONELLA CARBONARO, HANNO HILDMANN 15.1
INTRODUCTION V 411 15.2 PROBLEM DEFINITION AND FORMULATION 413 15.2.1
THE OBJECTIVE FUNCTION 414 15.2.2 A FOUR-INDICES MATHEMATICAL
FORMULATION 416 15.2.3 A SET PARTITIONING FORMULATION 418 15.2.4
REDUCTION RULES 418 15.3 THE ANTS METAHEURISTIC 420 15.3.1
ATTRACTIVENESS 421 15.3.2 TRAIL UPDATE 421 15.4 ANTS APPROACHES FOR THE
LCPP 422 15.4.1 ATTRACTIVENESS QUANTIFICATION 422 15.4.2 LOCAL
OPTIMIZATION 423 15.5 A DSS FOR THE LCPP 424 15.6 COMPUTATIONAL RESULTS
426 15.7 CONCLUSIONS 429 REFERENCES 430 CHAPTER 16: GENETIC ALGORITHMS
IN IRRIGATION PLANNING: A CASE STUDY OF SRI RAM SAGAR PROJECT, INDIA 431
K SRINIVASA RAJU AND D NAGESH KUMAR 16.1 INTRODUCTION 431 16.1.1 WORKING
PRINCIPLE OF GENETIC ALGORITHMS 432 16.1.2 NECESSITY OF MATHEMATICAL
MODELING IN IRRIGATION PLANNING 433 16.2 LITERATURE REVIEW '433 16.3
IRRIGATION SYSTEM AND MATHEMATICAL MODELING 434 16.3.1 CONTINUITY
EQUATION 436 16.3.2 CROP AREA RESTRICTIONS 436 16.3.3 CROP WATER
DIVERSIONS 436 16.3.4 CANAL CAPACITY RESTRICTIONS 437 16.3.5 LIVE
STORAGE RESTRICTIONS 437 16.3.6 CROP DIVERSIFICATION CONSIDERATIONS 437
16.4 RESULTS AND DISCUSSION 437 16.5 CONCLUSIONS 441 REFERENCES 443 |
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illustrated | Illustrated |
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isbn | 354020167X |
language | English |
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physical | XXII, 712 S. graph. Darst. : 24 cm |
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series | Studies in fuzziness and soft computing |
series2 | Studies in fuzziness and soft computing |
spelling | New optimization techniques in engineering Godfrey C. Onwubolu ; B. V. Babu Berlin [u.a.] Springer 2004 XXII, 712 S. graph. Darst. : 24 cm txt rdacontent n rdamedia nc rdacarrier Studies in fuzziness and soft computing 141 Literaturangaben Ingenieurwissenschaften Mathematisches Modell Engineering Mathematical models Mathematical optimization Prozessoptimierung (DE-588)4176074-8 gnd rswk-swf Optimierung (DE-588)4043664-0 gnd rswk-swf Technisches System (DE-588)4126276-1 gnd rswk-swf Technisches System (DE-588)4126276-1 s Optimierung (DE-588)4043664-0 s DE-604 Prozessoptimierung (DE-588)4176074-8 s Onwubolu, Godfrey C. Sonstige oth Studies in fuzziness and soft computing 141 (DE-604)BV021858135 141 GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012842812&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | New optimization techniques in engineering Studies in fuzziness and soft computing Ingenieurwissenschaften Mathematisches Modell Engineering Mathematical models Mathematical optimization Prozessoptimierung (DE-588)4176074-8 gnd Optimierung (DE-588)4043664-0 gnd Technisches System (DE-588)4126276-1 gnd |
subject_GND | (DE-588)4176074-8 (DE-588)4043664-0 (DE-588)4126276-1 |
title | New optimization techniques in engineering |
title_auth | New optimization techniques in engineering |
title_exact_search | New optimization techniques in engineering |
title_full | New optimization techniques in engineering Godfrey C. Onwubolu ; B. V. Babu |
title_fullStr | New optimization techniques in engineering Godfrey C. Onwubolu ; B. V. Babu |
title_full_unstemmed | New optimization techniques in engineering Godfrey C. Onwubolu ; B. V. Babu |
title_short | New optimization techniques in engineering |
title_sort | new optimization techniques in engineering |
topic | Ingenieurwissenschaften Mathematisches Modell Engineering Mathematical models Mathematical optimization Prozessoptimierung (DE-588)4176074-8 gnd Optimierung (DE-588)4043664-0 gnd Technisches System (DE-588)4126276-1 gnd |
topic_facet | Ingenieurwissenschaften Mathematisches Modell Engineering Mathematical models Mathematical optimization Prozessoptimierung Optimierung Technisches System |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012842812&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
volume_link | (DE-604)BV021858135 |
work_keys_str_mv | AT onwubolugodfreyc newoptimizationtechniquesinengineering |