GEATbx:

Main page Tutorial Algorithms M-functions Parameter/Options Example functions www.geatbx.com

GEATbx: Index

- - | - A - | - B - | - C - | - D - | - E - | - F - | - G - | - I - | - J - | - L - | - M - | - N - | - O - | - P - | - Q - | - R - | - S - | - T - | - V - | - W - | - X -

- -

feature selection 1
MAXONE problem 1
multi-objective optimization 1, 2
simple genetic algorithm 1

- A -

absolute position 1
absolute relation 1
Ackley's Path function

visualization 1

adaptation of strategy parameters 1
adaptation

mutation step sizes 1
search direction 1

aggregation

multiple objectives 1

analogy to fitness assignment 1
application of different strategies 1
Axis parallel hyper-ellipsoid function

visualization 1

- B -

Banana function

visualization 1

binary

parameter optimization 1
representation 1

boundaries 1, 2
boundaries (objexample1) 1
Branins's rcos function

visualization 1

- C -

classification of optimization problem 1
coding

binary variables 1

combination of integer and binary variables 1
combination of operators 1
combinatorial optimization 1
competing subpopulations 1
competition between subpopulations 1, 2
competition interval 1, 2
Competition options 1
competition rate 1, 2
competition selection 1
Competition.Do 1
Competition.Interval 1
Competition.Rate 1
Competition.SubpopMinimum 1
consumption factor 1
conversion of variables 1
conversion

variable representations 1

correlation between variables 1, 2

- D -

De Jong's function 1

visualization 1

De Jong's function 2

visualization 1

decoding of binary variables 1
Decreasing system size/dimension 1
definition of additional parameters 1
definition of input data 1
definition of output data 1
definition range of the variables 1
demo

demofun1 1
demogeatbx 1

dependencies between operators 1
determination of successful strategies 1
different representations 1, 2
dimension of problem 1
dimensionality of a problem 1
discrete recombination 1, 2
distribution of resources 1
distribution of the computational resources 1
distribution pressure 1
dividing the optimization problem into multiple tasks 1
division of resources 1, 2
dynamic distribution of resources 1

- E -

Easom's function

visualization 1

elitest selection 1, 2
elitist strategy 1
Entwicklung spezieller Operatoren 1
evolution strategies 1
extended competition model 1

- F -

fine mutation 1
fine search 1
fitness assignment 1, 2, 3

multi-objective 1, 2

fitness sharing 1
fitness values 1

- G -

generalized position recombination 1
generally adjustable procedures and operators 1
generation gap 1, 2
genetic algorithm

simple 1
steady state 1

genetic algorithms 1, 2
genetic drift 1
genotype 1

binary 1

globally oriented parameter optimization 1, 2
goal programming 1
Goldstein-Price's function

visualization 1

GPX 1
Griewangk's function

visualization 1

- I -

initial step size 1
Initialization options 1
innoculation 1
integer representation 1
interactive testing 1
invert mutation 1
investigation of system behavior 1
isolation period 1
isolation time 1

- J -

job shop scheduling 1, 2
JSS 1, 2, 3

- L -

Langermann's function

visualization 1

less successful subpopulation 1
linear ranking 1
local minima 1
locally oriented parameter optimization 1, 2

- M -

method of inequalities 1
Michalewicz's function

visualization 1

Migration options 1
migration rate 1
migration structure 1
migration time 1
Migration.Do 1
Migration.Interval 1
Migration.Rate 1
Migration.Selection 1
Migration.Topology 1
MOI 1
move mutation 1
Moved axis parallel hyper-ellipsoid function

visualization 1

multi-criteria problems 1
multi-dimensional visualization 1
multi-objective fitness assignment 1, 2
multi-objective optimization 1, 2, 3, 4, 5

aggregation 1
goal 1
goal programming 1
method of inequalities 1
PARETO-ranking 1
scalarization method 1
sharing 1
weighted sum 1

multi-objective ranking 1, 2, 3
multiple objective values 1, 2
multiple representations 1, 2
Mutation options 1
mutation precision 1, 2
mutation range 1, 2, 3, 4
mutation rate 1, 2, 3
Mutation.Name 1
Mutation.Precision 1
Mutation.Range 1
Mutation.Rate 1
mutation

fine 1
integer variables 1
real variables 1
rough 1

- N -

non-linear ranking 1
number of variables (objexample1) 1
NumberIndividuals 1
NumberSubpopulation 1

- O -

objective function 1
Objective function options 1
objective function properties 1
objective function

implementation (example) 1
implementation (objexample1) 1
special return values 1

one-dimensional slices 1
optimization options (objexample1) 1
optimization

multi-objective 1, 2

options

default 1

order of subpopulations 1

weighted 1

Output options 1
Output.GrafikInterval 1
Output.GrafikMethod 1
Output.GrafikStyle 1
Output.SaveBinDataFileName 1
Output.SaveBinDataInterval 1
Output.SaveTextExclude* 1, 2
Output.SaveTextFileName 1
Output.SaveTextInterval 1, 2
Output.StatePlotFunction 1
Output.StatePlotInterval 1
Output.TextExclude* 1, 2
Output.TextInterval 1, 2
output

graphical - during an optimization 1
graphical - first obj. function 1
text - during an optimization 1
text - end of optimization 1
text - start of optimization 1

- P -

parameter identification 1
parameter optimization 1

binary 1
globally oriented 1, 2
locally oriented 1
binary variables 1
different representations 1, 2
locally oriented 1

PARETO- dominance 1
PARETO-optimality 1
PARETO-ranking 1
partial matching crossover 1
phenotype 1

integer 1
real 1

plt 1
PMX 1
population size 1
premature convergence 1
pretty print 1
problem classes 1, 2
problem-specific visualization 1
production scheduling 1
prprintf 1

- Q -

QAP 1, 2
quadratic assignment problem 1

- R -

rank of subpopulation 1, 2
rank-based fitness assignment 1
ranking 1
Ranking 1
ranking

multi-objective 1, 2

Rastrigin's function

visualization 1

Recombination options 1
recombination rate 1, 2
Recombination.Name 1
Recombination.Rate 1
recombination

generalized position 1
partial matching 1

reduced surrogate 1
reduction of number of variables 1
regional population model 1
relative relation 1
representation

binary 1, 2
conversion 1
different 1, 2
integer 1, 2
integer and binary 1
multiple 1, 2
ordering 1
permutation 1
real 1, 2
real and integer and binary 1

resource consumption 1, 2
resources 1
Result options 1
robust parameterization 1
Rosenbrock's function

visualization 1

Rotated hyper-ellipsoid function

visualization 1

rough mutation 1
rough search 1
run time options 1
Run.BestObjectiveValue 1
Run.CountObjFun 1
Run.DoTerminate 1
Run.Generation 1

- S -

Sammon-Mapping 1
scalability of problem 1
scalarization method 1
Schwefel's function

visualization 1

scramble mutation 1
search space 1
selection 1
Selection options 1
Selection.GenerationGap 1
Selection.LocalDimension 1
Selection.LocalDistance 1
Selection.LocalTopology 1
Selection.Name 1
Selection.Pressure 1
Selection.RankingMethod 1
Selection.RankingMultiobj 1
Selection.ReinsertionMethod 1
Selection.ReinsertionRate 1
selection

elitest 1
truncation selection 1

SGA 1, 2
sharing 1
simple genetic algorithm 1
simulation of several data records 1
single-objective optimization 1
Six-hump camel back function

visualization 1

size of a problem 1
solving optimization problems 1
special procedures and operators 1
Special.CollectBest.Compare 1
Special.CollectBest.FileName 1
Special.CollectBest.Interval 1
Special.CollectBest.Rate 1
Special.CollectBest.WriteFile 1
Special.InitDo 1
Special.InitFunction 1
Special.InitPresetKeep 1
Special.InitPresetRand 1
Special.InitUniformCreate 1
status

during run 1
header 1
result 1

steady state 1
steady state genetic algorithm 1
straddtime 1
subdividing an optimization problem 1
subpopulation minimum 1, 2
success of subpopulation 1
Success of subpopulations 1
successful subpopulation 1
Sum of different power function

visualization 1

supplementary strategies 1
swap mutation 1
System.ObjFunAddPara 1
System.ObjFunDescription 1
System.ObjFunFilename 1
System.ObjFunGoals 1
System.ObjFunMinimum 1
System.ObjFunVarBoundOut 1
System.ObjFunVarBounds 1

- T -

Termination options 1
Termination.Cluster 1
Termination.Diff2Optimum 1
Termination.GoodWorstObjV 1
Termination.Kappa 1
Termination.MaxGenerations 1
Termination.MaxTime 1
Termination.Method 1
Termination.Phi 1
Termination.RunningMean 1
Termination.StdObjV 1
text output 1
traveling sales person 1
travelling sales person 1
truncation selection 1
TSP 1, 2, 3
two-dimensional slices 1

- V -

VariableFormat 1, 2, 3, 4
vehicle routing problem 1
vehicle routing problems 1
Visualization options 1
VLUB 1
VRP 1, 2

- W -

way through solution domain 1
way through the search space 1
weighted sum 1

- X -

XCS819

84 1, 2, 3

GEATbx:

Main page Tutorial Algorithms M-functions Parameter/Options Example functions www.geatbx.com

This document is part of version 3.8 of the GEATbx: Genetic and Evolutionary Algorithm Toolbox for use with Matlab - www.geatbx.com.
The Genetic and Evolutionary Algorithm Toolbox is not public domain.
© 1994-2006 Hartmut Pohlheim, All Rights Reserved, (support@geatbx.com).