Genetic algorithms and engineering optimization:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Wiley
2000
|
| Schriftenreihe: | Wiley series in engineering design and automation
A Wiley-Interscience publication |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XVI, 495 S. graph. Darst. |
| ISBN: | 0471315311 |
Internformat
MARC
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| 245 | 1 | 0 | |a Genetic algorithms and engineering optimization |c Mitsuo Gen ; Runwei Cheng |
| 264 | 1 | |a New York [u.a.] |b Wiley |c 2000 | |
| 300 | |a XVI, 495 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
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Datensatz im Suchindex
| _version_ | 1804128631747772416 |
|---|---|
| adam_text | CONTENTS
Preface xiii
1 Foundations of Genetic Algorithms 1
1.1 Introduction 1
1.1.1 Encoding Issue 2
1.1.2 Genetic Operators 7
1.1.3 Selection 9
1.1.4 Genetic Local Search 11
1.2 Adaptation of Genetic Algorithms 14
1.2.1 Structure Adaptation 15
1.2.2 Parameter Adaptation 16
1.2.3 Fuzzy Logic Controller 18
1.3 Genetic Optimizations 27
1.3.1 Global Optimizations 27
1.3.2 Constrained Optimizations 34
1.3.3 Combinatorial Optimizations 38
1.3.4 Multiobjective Optimizations 39
1.4 Recent Genetic Algorithm Dissertations 40
2 Combinatorial Optimization Problems 53
2.1 Introduction 53
2.2 Set Covering Problem 53
2.2.1 Airline Crew Scheduling Problems 56
2.2.2 Genetic Representation 56
2.2.3 Genetic Operators 58
2.2.4 Genetic Algorithm 60
2.2.5 Computational Experience 61
2.3 Bin Packing Problem 61
2.3.1 Heuristic Algorithms 63
vii
viii CONTENTS
2.3.2 Genetic Representation 65
2.3.3 Genetic Operators 68
2.3.4 Fitness Function 69
2.3.5 Initial Population 69
2.3.6 Computational Experience 70
2.4 Knapsack Problem 71
2.4.1 Multiple Choice Knapsack Problem 72
2.4.2 Multiconstraint Knapsack Problem 77
2.5 Minimum Spanning Tree Problem 81
2.5.1 Quadratic Minimum Spanning Tree Problem 82
2.5.2 Degree Constrained Minimum Spanning Tree Problem 85
2.5.3 Bicriteria Minimum Spanning Tree Problem 90
3 Multiobjective Optimization Problems 97
3.1 Introduction 97
3.2 Basic Concepts of Multiobjective Optimizations 97
3.2.1 Nondominated Solutions 98
3.2.2 Preference Structures 101
3.2.3 Basic Solution Approaches 102
3.2.4 Structures and Properties of Problems 106
3.3 Genetic Mulitobjective Optimization 106
3.3.1 Features of Genetic Search 106
3.3.2 Fitness Assignment Mechanism 107
3.3.3 Fitness Sharing and Population Diversity 111
3.3.4 The Concept of Pareto Solution 113
3.4 Vector Evaluated Genetic Algorithms 115
3.5 Pareto Ranking and Tournament Methods 118
3.5.1 Pareto Ranking Method 118
3.5.2 Pareto Tournament Method 122
3.6 Weighted Sum Approach 124
3.6.1 Random Weight Approach 125
3.6.2 Adaptive Weight Approach 127
3.7 Distance Method 131
3.7.1 General Idea of the Distance Method 131
3.7.2 Calculation of Distance Measure 133
3.7.3 Application of the Distance Method 136
3.8 Compromise Approach 136
3.9 Goal Programming Approach 138
CONTENTS ix
4 Fuzzy Optimization Problems 142
4.1 Introduction 142
4.2 Fuzzy Linear Programming 143
4.2.1 Fuzzy Linear Programming Model 143
4.2.2 Genetic Algorithm Approach 149
4.2.3 Interactive Approach 152
4.2.4 Numerical Example 154
4.3 Fuzzy Nonlinear Programming 156
4.3.1 Nonlinear Programming Model 157
4.3.2 Inexact Approach to FO/RNP 1 161
4.3.3 Interactive Approach 163
4.3.4 Numerical Example 164
4.4 Fuzzy Nonlinear Mixed Integer Goal Programming 165
4.4.1 Fuzzy Nonlinear Mixed Integer Goal Programming
Model 168
4.4.2 Genetic Algorithm Approach 170
4.4.3 Numerical Examples 173
4.5 Fuzzy Multiobjective Integer Programming 178
4.5.1 Problem Formulation 181
4.5.2 Augmented Minimax Problems 184
4.5.3 Genetic Algorithm Approach 185
4.5.4 Interactive Fuzzy Satisfaction Method 189
4.5.5 Numerical Example 190
5 Reliability Design Problems 194
5.1 Introduction 194
5.2 Network Reliability Design 195
5.2.1 Problem Formulation 196
5.2.2 Dengiz, Altiparmak, and Smith s Approach 198
5.2.3 Deeter and Smith s Approach 204
5.3 Tree Based Network Reliability and LAN Design 211
5.3.1 Bicriteria Network Topology Design 212
5.3.2 Numerical Examples 219
5.4 Multiobjective Reliability Design 221
5.4.1 Bicriteria Reliability Design 221
5.4.2 Genetic Algorithm Approach 224
5.4.3 Hybrid Genetic Algorithm Approach 226
5.4.4 Reliability Design with Fuzzy Goals 230
x CONTENTS
6 Scheduling Problems 235
6.1 Introduction 235
6.2 Job Shop Scheduling 235
6.2.1 Basic Approaches 236
6.2.2 Encodings 236
6.2.3 Adapted Genetic Operators 238
6.2.4 Heuristic Featured Genetic Operators 242
6.2.5 Hybrid Genetic Algorithms 244
6.2.6 Discussion 251
6.3 Grouped Job Scheduling Problem 253
6.3.1 Problem Description and Necessary Condition 253
6.3.2 Fundamental Runs 255
6.3.3 Representation 257
6.3.4 Evaluation 259
6.3.5 Genetic Operators 260
6.3.6 Overall Procedure 260
6.3.7 Numerical Example 261
6.4 Resource Constrained Project Scheduling 263
6.4.1 Priority Based Encoding 265
6.4.2 Genetic Operators 270
6.4.3 Evaluation and Selection 272
6.4.4 Experimental Results 274
6.5 Parallel Machine Scheduling 278
6.5.1 Dominance Condition 280
6.5.2 Memetic Algorithms 284
6.5.3 Experimental Results 287
6.6 Multiprocessor Scheduling 288
6.6.1 Problem Description and Assumptions 289
6.6.2 Genetic Algorithm for MSP 290
6.6.3 Numerical Example 295
7 Advanced Transportation Problems 297
7.1 Introduction 297
7.1.1 Transportation Model 297
7.1.2 Formulation of Transportation Problems 299
7.2 Spanning Tree Based Approach 304
7.2.1 Tree Representation 304
7.2.2 Initialization 306
7.2.3 Genetic Operators 308
CONTENTS xi
7.2.4 Evaluation and Selection 308
7.2.5 Overall Procedure 311
7.3 Multiobjective Transporation Problem 311
7.3.1 Problem Description 312
7.3.2 Spanning Tree Based Genetic Algorithm for
Multiobjective Transportation Problem 313
7.3.3 Numerical Examples 316
7.4 Fixed Charge Transportation Problem 320
7.4.1 Mathematical Model 321
7.4.2 Difficulty of fcTP Instances 321
7.4.3 Solution Method for the fcTP 322
7.4.4 Implementation of the Genetic Algorithm 322
7.4.5 Numerical Examples 323
7.5 Capacitated Plant Location Problem 325
7.5.1 Mathematical Model 326
7.5.2 Spanning Tree Based Genetic Algorithm for Plant
Location Problems 328
7.5.3 Numerical Examples 329
7.6 Bicriteria Transportation Problem with Fuzzy Coefficients 330
7.6.1 Problem Description 331
7.6.2 Ranking Fuzzy Numbers 332
7.6.3 Implementation of the Genetic Algorithm 333
7.6.4 Numerical Examples 336
8 Network Design and Routing 341
8.1 Introduction 341
8.2 Shortest Path Problem 341
8.2.1 Problem Formulation 342
8.2.2 Genetic Algorithm Approach 343
8.2.3 Numerical Examples 351
8.3 Adaptive Network Routing 352
8.3.1 Genetic Based Adaptive Routing 353
8.3.2 Representation of Chromosomes 354
8.3.3 Evaluation of Chromosomes 355
8.3.4 Genetic Operators 355
8.3.5 Numerical Examples 360
8.4 Centralized Network Design 363
8.4.1 Problem Formulation 364
8.4.2 Genetic Algorithm Approach 365
8.4.3 Numerical Example 366
xii CONTENTS
8.5 Computer Network Expansion 366
8.5.1 Problem Description 368
8.5.2 Kummar, Pathak, and Gupta s Approach 369
8.5.3 Numerical Example 373
8.6 Multistage Process Planning 373
8.6.1 Problem Description 374
8.6.2 Genetic Algorithm Approach 376
8.6.3 Numerical Examples 377
8.7 M/G/s Queuing Facility Location on a Network 378
8.7.1 Problem Description 379
8.7.2 Evolutionary Computation Approach 383
8.7.3 Numerical Examples 387
9 Manufacturing Cell Design 390
9.1 Introduction 390
9.2 Manufacturing Cell Design 391
9.3 Traditional MCD Approaches 393
9.3.1 Similarity Coefficient Methods 394
9.3.2 Array Based Methods 395
9.3.3 Mathematical Programming Methods 395
9.3.4 Graph and Network Methods 396
9.4 Genetic Algorithm Approaches 396
9.4.1 Representative and Genetic Operators 396
9.4.2 Joines Order Based Approach 399
9.4.3 Moon and Kim s Approach 405
9.4.4 Joines Integer Programming Formulation Approach 410
9.4.5 Other Approaches 419
9.5 Cell Design with Alternative Process Plans 419
9.5.1 Incorporation of Alternative Operations and Machine
Redundancy 421
9.5.2 Incorporation of Alternative Routings 424
9.5.3 Moon, Gen, and Kim s Approach to Independent Cells 433
9.6 Designing Independent Cells 438
9.6.1 Family Formation for Minimizing Number of Machine
Types 439
9.6.2 Determining Number of Families 443
9.6.3 Minimizing Number of Machines 448
9.6.4 Other Considerations 449
References 451
Index 491
|
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| author | Gen, Mitsuo 1944- Cheng, Runwei |
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| isbn | 0471315311 |
| language | English |
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| spelling | Gen, Mitsuo 1944- Verfasser (DE-588)13630706X aut Genetic algorithms and engineering optimization Mitsuo Gen ; Runwei Cheng New York [u.a.] Wiley 2000 XVI, 495 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Wiley series in engineering design and automation A Wiley-Interscience publication Genetischer Algorithmus (DE-588)4265092-6 gnd rswk-swf Genetischer Algorithmus (DE-588)4265092-6 s DE-604 Cheng, Runwei Verfasser aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009439946&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Gen, Mitsuo 1944- Cheng, Runwei Genetic algorithms and engineering optimization Genetischer Algorithmus (DE-588)4265092-6 gnd |
| subject_GND | (DE-588)4265092-6 |
| title | Genetic algorithms and engineering optimization |
| title_auth | Genetic algorithms and engineering optimization |
| title_exact_search | Genetic algorithms and engineering optimization |
| title_full | Genetic algorithms and engineering optimization Mitsuo Gen ; Runwei Cheng |
| title_fullStr | Genetic algorithms and engineering optimization Mitsuo Gen ; Runwei Cheng |
| title_full_unstemmed | Genetic algorithms and engineering optimization Mitsuo Gen ; Runwei Cheng |
| title_short | Genetic algorithms and engineering optimization |
| title_sort | genetic algorithms and engineering optimization |
| topic | Genetischer Algorithmus (DE-588)4265092-6 gnd |
| topic_facet | Genetischer Algorithmus |
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