Michalewicz Z. — Genetic algorithms + data structures = evolution programs :: Электронная библиотека попечительского совета мехмата МГУ

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Michalewicz Z. — Genetic algorithms + data structures = evolution programs

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Название: Genetic algorithms + data structures = evolution programs

Автор: Michalewicz Z.

Аннотация:

Zbigniew Michalewicz's Genetic Algorithms + Data Structures = Evolution Programs has three sections. The first section is a straightforward introduction to genetic algorithms. In the second section, Michalewicz describes how to apply genetic algorithms to numerical optimization. Michalewicz, who is a pioneer in this field, discusses the rationale for using genetic algorithms for numerical optimization and describes several experiments that show how this new type of genetic algorithm performs. The author devotes the third section of the book to evolution programs.

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Рубрика: Computer science/Генетика, нейронные сети/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Издание: 3rd, revised and extended edition

Год издания: 1996

Количество страниц: 387

Добавлена в каталог: 19.11.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID

Предметный указатель

1/5 success rule      161
15% replacement rule      321
5% replacement rule      83 85
Aarts, E.H.L.      68
Abuali, F.N.      262
Adaptive control      15
Affinity test      175
Allele      15
Arabas, J.      119
ARGOT strategy      119 175
Arithmetical crossover      112 128 166 323
Attia, N.F.      135
Automatically Defined Functions      287
Axelrod, R.      22—24
Baeck, T.      ix 61
Baker, J.E.      59
Baldwin effect      320
Banach fixpoint theorem      68
Bean, J.C.      151
Beasley, D.      169
Beasley, J.      263
Behavioral memory      324
Belew, R.      93 174
Beltramo, M.A.      249
Bersini, H.      91
Bertoni, A.      54
Bilchev, G.      157
Bin Packing Crossover Operator      252
Boltzmann distribution      28
Boltzmann selection      61
Booker, L.B.      15 269
Boolean Satisfiability Problem (SAT)      30 315
Boundary mutation      127
Bowen, J.      326
Breeder genetic algorithms      65 330
Brindle, A.      59
Broyden, C.G.      135
Bui, T.N.      264 309
Building block hypothesis      53
Bull, D.R.      169
Burke, E.K.      247
Cauchy sequence      70
Cetverikov, S.S.      14
Christofides, N.      210
Chromosome      15
Chromosome, age of      72
Chromosome, lifetime parameter      73
Chromosome, variable length      4 257 275
Classifier system      65 270
CNF-satisfiability problem      210
Co-evolutionary systems      332
Cognitive modeling      15
Communication network      4
Constraint satisfaction problem      326
Constraints      5 312
Constraints, linear      123
Constraints, nonlinear      134 141 154
Constraints, penalty functions      82 141
Constraints, repair algorithms      83 154
Coombs, S.      4
Correns, K.      14
Craighurst, R.      235
Crossover      17 39 49
Crossover, alternating-edges      212
Crossover, arithmetical      112 128 166 323
Crossover, CX      218 309
Crossover, edge recombination      221 309
Crossover, edge recombination, enhanced      223 309
Crossover, guaranteed average      166
Crossover, heuristic      129 213
Crossover, intermediate      166
Crossover, intersection      224
Crossover, multi-point      89
Crossover, MX      231
Crossover, one point      76 89
Crossover, order-based      219
Crossover, OX      217 251 309
Crossover, PMX      188 216 251 309
Crossover, position based      219
Crossover, probability of      35
Crossover, segmented      89
Crossover, shuffle      89
Crossover, simple      112
Crossover, simplex      91
Crossover, structured      248
Crossover, subtour-chunks      213
Crossover, two-point      89
Crossover, uniform      90
Crossover, union      224
Cultured algorithms      153 333
Darwen, P.      25
Darwin, C.      14
Database      15
Database, query optimization      15
Davidor, Y.      254
Davis, L.      4 8 9 13 217 241 243 245 248
Davis, T.E.      68
Dawkins, R.      334
De Jong, K.A.      vii 3 6 15 59 90 269 312 316
De Vries, H.      14
Death penalty      144 319
Deb, K.      172
Deception      54 331
Decoders      84 323
Delta Coding algorithm      93 119 173
Diploidy      15 332
Divide and conquer      236
Dominance      15
Don't care symbol      45
Dorigo, M.      54
Dozier, G.      326
Dynamic control      100
dynamic parameter encoding      93 119 174 331
Eiben, A.E.      68 91 326
Environment      17
Epistasis      54
Eppley, P.H.      264
Esbensen, H.      263
Eshelman, L.J.      58 90 331
EVA programming environment      10 306
Evaluation function      20 312
Evolution program      1 5
Evolution strategies      1 160 310
Evolution strategies versus genetic algorithm      164
Evolution strategies, $(\mu + \lambda)$       162
Evolution strategies, $(\mu, \lambda)$       162
Evolution strategies, multi-membered      162
Evolution strategies, operators      163
Evolution strategies, two-membered      161
Evolutionary programming      1 119 176 283 310 323
Exploitation      15
Exploration      15
Falkenauer, E.      251 253
Fiacco, A.V.      134
Finite state machine      283
Fitness      17
Fitness distance correlation      331
Fleming, P.J.      172
Fogel, D.B.      ix 176
Fogel, L.J.      1 283 336
Fonseca, C.M.      172
Fox, B.R.      223
Fox, M.S.      242
Function optimization      18 330
Fuquay, D'A.      221
game playing      15
GAMS      108 294
Gene      15
Gene pool recombination      91
Gene scanning      91

General Problem Solver      7
Genesis      67 106 172 295 303
Genetic algorithm      13 17
Genetic algorithm versus evolution strategy      164
Genetic algorithm with varying population size      72
Genetic algorithm, binary representation      97
Genetic algorithm, contractive mapping      68
Genetic algorithm, crossover      35
Genetic algorithm, evaluation function      17 38
Genetic algorithm, example      26
Genetic algorithm, floating point representation      97 99
Genetic algorithm, interval      119 176
Genetic algorithm, messy (mGA)      92 331
Genetic algorithm, modified      62
Genetic algorithm, mutation      35
Genetic algorithm, operators      17 21 91
Genetic algorithm, parameters      18 21 91
Genetic algorithm, population size      72
Genetic algorithm, representation      4 17 19 33 97
Genetic algorithm, representation, direct      246
Genetic algorithm, representation, indirect      246
Genetic algorithm, simple (SGA)      76
Genetic algorithm, steady state      65
Genetic algorithm, structure      17
Genetic inductive learning      267 276
Genetic programming      1 285 310 323
GENETIC-1      188
GENETIC-1, evaluation function      187
GENETIC-1, initialization      185
GENETIC-1, operators      187
GENETIC-2      191 311
GENETIC-2, evaluation function      189 196
GENETIC-2, initialization      189 196
GENETIC-2, operators      189 196
GENETIC-2, representation      188 196
Genetics, history      14
genitor      303
GENOCOP      124 167
GENOCOP II      134
GENOCOP III      154
Genotype      15
Giordana, A.      281
Glover, D.E.      6
Glover, F.      1 175 176 325
Goldberg, D.E.      3 15 65 68 72 76 91 93 97 168 174 216
Gorges-Schleuter, M.      234
Granularity evolution      119 176
Gray coding      98
Greene, F.      15
Grefenstette, J.J.      72 91 174 221 295
Guan, S.      220 223 231
Hadj-Alouane, A.B.      151
Hamming cliff      106
Haploidy      15
Heredity      14
Heuristic methods      307
Hillclimbing      15 16 26
Hinterding, R.      119
Hoffmeister, F.      61 297
Holland, J.H.      1 3 4 54 107 220 269
Homaifar, A.      142 220 223 231
Houck, C.R.      142
Husbands, P.      245
Hybrid genetic algorithms      9 310
Hyperplane      45
Ibaraki, T.      265
Immune recruitment mechanism      119 175
Implicit parallelism      54 97
incest prevention      58 235
Industrial engineering      265
Interval genetic algorithm      176
inversion      55 219
Janikow, C.      267
Jenkins nightmare      14
Jenkins, F.      14
Joines, J.A.      142
Jones, A.J.      236
Jones, D.R.      241 249
Jones, T.      265
Juliff, K.      265
Karp, R.M.      210 236
Keane, A.      156
Kershenbaum, A.      261
Kingdon, J.      68
Koza, J.R.      1 4 285 287
Kraemer, O.      234
Lagrangian relaxation      152
Lamarckian evolution      320
Le Riche, R.      153
Lidd, M.L.      211
Lin — Kernighan algorithm      210
Lingle, R.      216
Litke, J.D.      210
Locus      15
Luchian, H.      247
Machine learning      267
Mahfoud      170
Maintaining feasibility      322
Management science      265
Maniezzo, V.      176
Manner, R.      336
Markov chain      68
Martin, R.R.      169
Martin, W.      235
Massively parallel GAs      333
Maximum clique problem      264
McCormick, G.P.      134
McMahon, M.B.      223 242
Mendel, G.      14
Meta genetic algorithm      91
Michigan approach      269 270
Mill, F.      245
Mohammed      8
Moon, B.R.      309
Morgan, T.      14
Morishima, A.      89
Muehlenbein, H.      65 91 234 249 333
Muitiobjective optimization      171
Multi-parent operators      91
Multimodal optimization      168
Murray, W.      135
Musseli, M.      176
Mutation      17 41 51
Mutation of order k      247
Mutation rate      21
Mutation, day      247
Mutation, deletion      260
Mutation, insertion      260
Mutation, non-uniform      103 111 128
Mutation, probability of      35
Mutation, rate      17
Mutation, scramble sublist      244
Mutation, smooth      260
Mutation, structural      248
Mutation, swap      260
Mutation, uniform      111 127
Natural selection      14
Navigation      253
Neural network      4
Ng, K.P.      15
Niche methods      168
Nissen, V.      265
Non-random mating      331
NSGA      172
Oliver, I.M.      218
OOGA      303
Operators, cut      92
Operators, splice      92
Optimal control      15
Optimal control, harvest problem      109 113 115

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