Главная    Ex Libris    Книги    Журналы    Статьи    Серии    Каталог    Wanted    Загрузка    ХудЛит    Справка    Поиск по индексам    Поиск    Форум   
blank
Авторизация

       
blank
Поиск по указателям

blank
blank
blank
Красота
blank
Cantu-Paz E. — Efficient and accurate parallel genetic algorithms
Cantu-Paz E. — Efficient and accurate parallel genetic algorithms

Читать книгу
бесплатно

Скачать книгу с нашего сайта нельзя

Обсудите книгу на научном форуме



Нашли опечатку?
Выделите ее мышкой и нажмите Ctrl+Enter


Название: Efficient and accurate parallel genetic algorithms

Автор: Cantu-Paz E.

Аннотация:

The book can be read in several ways, depending on the readers' interests and their previous knowledge about these algorithms. Newcomers to the field will find the background material in each chapter useful to become acquainted with previous work, and to understand the problems that must be faced to design efficient and reliable algorithms. Potential users of parallel GAs that may have doubts about their practicality or reliability may be more confident after reading this book and understanding the algorithms better. Those who are ready to try a parallel GA on their applications may choose to skim through the background material, and use the results directly without following the derivations in detail. These readers will find that using the results can help them to choose the type of parallel GA that best suits their needs, without having to invest the time to implement and test various options. Once that is settled, even the most experienced users dread the long and frustrating experience of configuring their algorithms by trial and error. The guidelines contained herein will shorten dramatically the time spent tweaking the algorithm, although some experimentation may still be needed for fine-tuning.


Язык: en

Рубрика: Computer science/Генетика, нейронные сети/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2000

Количество страниц: 162

Добавлена в каталог: 11.11.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
blank
Предметный указатель
$(\mu\mathop{,}\limits^{+}\lambda)$ selection      99
$\Delta$      see "Topology degree"
$\gamma$ computation/communication ratio      38
$\rho$      see "Migration rate"
Abramson, D.      35
Absorbing barriers      20
Absorbing state      71 73
Absorption probability      72
Absorption time      71
Adamidis, P.      6 52
Additive fitness function      18
Additive fitness functions      16
Aggregate population size      90
Alba, E.      6
Algorithmic benefits      10
Alleles      5
Alphabet      5
Anderson, E.J.      124
Andre, D.      116
Approximate fitness      28
ASPARAGOS      123
assumptions      21 54 57 83 90 144
Asynchronous      10 34
Average fitness      102
Baeck, T.      30 36 99 103
Baker, J.E.      98
Baluja, S.      24 122 124
Bandwidth      38
Bayesian optimization algorithm      26
bb      see "Building blocks"
Belding, T.      117
Bennett, F.      11
Beowulf      11 54
Bethke, A.      34
bi-directional ring      77 92
Bianchini, R.      129
Bin packing      124
binary strings      5
binomial      56
Binomial distribution      69 83 103
Biological implications      9
Booker, L.      98
Bossert, W.      50
Bound      80
Bounding case      45 49—65 86
bounds      143
Branke, J.      122
Braud, A.      46
Braun, H.C.      51
Brindle, A.      99
building blocks      5—6 14
Building blocks, correct      6 68
Building blocks, critical number      82 83
Building blocks, deciding between      14 17—20
Building blocks, expected number      15 21 68
Building blocks, mixing      15 24
Building blocks, supply      15 24 27
Calegari, P.      10
Capcarrerre, M.      126
Cartwheel topology      91
Catastrophe      143
Cellular GAs      9 122
Cellular programming      126
Central limit theorem      18
Chakraborty, U.K.      44
Chromosome      2
Classification      see "Parallel GAs"
coarse-grained      7 49
Cohoon, J.P.      8
Collateral noise      17 20
Colonization      143
Communication time      37
Community model      129
Compact GA      24
Competition      18 21
Compression      143
Computation time      37
Conclusions      143—145
Connection Machine      122 125
Contributions      144
Controversy on speedups      54
Critical path      125
Crossover      3 4 16 23 24 27
Darwinian evolution      4
Davidor, Y.      10
Davison, B.D.      45
De Jong, K.      17 44
Deb, K.      25
Deception      5
Deceptive      see "Deceptive function"
Deceptive functions      25 68 80
Decomposition      14
Degree      76 80 82 92
Deme      7
Deme count      49
Diameter      142
Difference equation      101
Diffusion      9 122
Disruption      26
Dissertation      ix
Distributed memory      35 49
Diversity      51 52
Dymek, A.      54
Dynamic environment      51
Dynamic neighborhoods      142
Efficiency      39 52
Eiben, A.E.      4
Elredge, N.      8
Embarrassingly parallel      1
Emigrants      105
encodings      3
Epoch      60 67 80
Epochs, multiple      68 88 91
Epochs, until convergence      71 95
Ethernet      42
Etxeberria, R.      143
Evolution strategies      36 54 126
Evolutionary programming      36
Exact models      143
execution time      37—38 83 94
Exponential time      143
Extended compact GA      26
Extended neighborhood      89—91 95
Extensions      141—143
Facet      14 143
Fair comparisons      55
Fast messy GAs      54
fine-grained      9 122—126
Fitness distribution      18
Fitness function      3 18
Fitness-proportionate selection      98
Fixed topology      96
Fogarty, T.      35
Fully-connected demes      58—64 68—74 80 86—87
Fundamental matrix      71
Gambler's ruin      13—31 57 60 68 80 92
Gambler's ruin, assumptions      21
Gambler's ruin, extensions      141
Gaussian      56
Generation      21
Generation gap      44
Generations until convergence      104 108
Genetic algorithms      2—5
Genetic programming      36 54
genitor      44
Global parallel GAs      7
Goldberg, D.E.      3 14 17 54 99 114 129
Goodman, E.      53
Gordon, V.S.      10 125
Gorges-Schleuter, M.      123
Grefenstette, J.      34 50 127
grid      9
Grosso, P.      51
Gruau, F.      127
Hamming distance      98
Hancock, P.      99
Hardware      11 38 94
Harik, G.      3 13 26
Hart, W.      9 126
Hauser, R.      35
Herrera, F.      52
Heterogeneous algorithm      53
Heuristic      3
hierarchical      10 126—134
hierarchical topology      53
Hillis, D.      125
Hirsh, J.      36
Holland, J.      15 98
Hybrid      10 34 126—134
Hypercube      77
Hypergraphs      125
Identity matrix      71
Immediate neighbors      88 90
Implicit parallelism      15
Independent partitions      19
Indirect contribution      88
Injection island      53
Intensity      see "Selection"
Island model      7 49
Isolated demes      51 55—58
Iterated gambler's ruin      68
Job shop scheduling      124
Kargupta, H.      26
Kirley, M.      123 142
Koza, J.      53 116
Kroeger, B.      124
landscape      143
latency      38
Learning problem structure      143
Levine, D.      53
limitations      104 144
Lin, S.C.      52 128
Linear ranking      99
Linear speedups      131
Linkage      26
Linkage equilibrium      24
Literature reviews      6
Little model      15
Locus      5
Long run      70 95
Macroscopic variables      104
Mahfoud, S.      142
Manderick, B.      122
Markov chains      44 53 69 92 95
Massively Parallel      122
Master      see "Master-slave"
master-slave      7 33—48 64
Mathematica      108 133
Mating pool      99
Mating restriction      142
Merkle, L.      54
mesh      122
Mesh shape      142
Messy GAs      26 54
Migrants      97
Migration      7
Migration rate      82
Migration, frequency      49 51 58
Migration, policy      60 97
Migration, rate      49 59 73—74
Miller, B.      30 103
Mixing      14
Mixing coefficient      90 92
Modern GAs      26 143
Muehlenbein, H.      10 16 24 97 103 143
Multi-modal problems      142
Multi-objective problems      125 142
Multi-parent recombination      4
Multimodal problems      125
Multiple epochs      88
Multiple populations      see "Multiple-deme"
Multiple-deme      7
Munetomo, M.      51
Mutation      3 16 23 36
Near-linear speedups      36 40
Neighborhood      76
Neighborhood radius      123
Neighborhood size      123
Neural network      42
Niching      142
Noise      17 23 28
Noise, collateral      17 20
Noisy problem      28
Non-uniformly scaled problems      25
Normal distribution      18 28 83 106
Normal distribution, approximation      22 84
Ochoa, G.      30
One-max      23 28 103 111
Oppacher, F.      50
Optimal degree      85 94
Optimal deme size      85
Optimal mutation rate      97
Optimal number of demes      86 95
Optimal number of epochs      94
Optimal number of slaves      38
Order      see "Schema order"
Order statistics      56 105
Oussaidene, M.      36 53
Overlapping substrings      27
Panmictic groups      90
Panmictic unit      45
Parallel efficiency      see "Efficiency"
Parallel GAs, classification      6
Parallel operators      36
Parallel speedup      see "Speedup"
parents      98
Partition      5 20 60
PBIL      24
Pelikan, M.      143
Persistent state      71
Pettey, C.      51 53 98 122
Pollination model      98
Population      2 13
Population genetics      8
Population size      142
Population, size      3 13—31 49
Population, structure      9
Premature convergence      51
Probabilistic models      143
Probability of absorption      72
Probability of deciding correctly      18
Probability of success      20 69 72 76
Probability of success in the long run      71
Probability, transition      70
Problem classes      142
Problem difficulty      13 23 25 27
Problem size      13 16 23
Proportional selection      30 46
Proportionate selection      99
Punch, W.      10 35 53 98
Punctuated equilibria      8
PVM      42
Qi, X.      24
Random deletion      143
Random walk      13 20
Rank-based selection      98
Rastrigin function      53
Recombination      36
Rectangular grid      122
Reducing selection pressure      110
1 2
blank
Реклама
blank
blank
HR
@Mail.ru
       © Электронная библиотека попечительского совета мехмата МГУ, 2004-2018
Электронная библиотека мехмата МГУ | Valid HTML 4.01! | Valid CSS! О проекте