# Input file for the GA Toolbox
# Author: Kumara Sastry
# Date: April, 2006
#

#
# GA type: SGA or NSGA
#
NSGA

#
# Number of decision variables
#
3

#
# For each decision variable, enter: 
# 	decision variable type, Lower bound, Upper bound	 
# Decision variable type can be double or int
#
double -5.0 5.0
double -5.0 5.0
double -5.0 5.0

#
# Objectives: 
#	Number of objectives
#	For each objective enter the optimization type: Max or Min
#
2
Min
Min

#
# Constraints:
#	Number of constraints
#	For each constraint enter a penalty weight 
#
0

#
# General parameters: If these parameters are not entered default
#                     values will be chosen. However you must enter 
#                     "default" in the place of the parameter.
#	[population size]
#	[maximum generations]
#	[replace proportion]
#
400
250
0.9

#
# Niching (for maintaining multiple solutions)
# To use default setting type "default"
#  Usage: Niching type, [parameter(s)...]
#  Valid Niching types and optional parameters are:
#	NoNiching
#	Sharing [niching radius] [scaling factor]
#	RTS [Window size]
#	DeterministicCrowding
#
#  When using NSGA, it must be NoNiching (OFF).
#
NoNiching

#
# Selection
#  Usage: Selection type, [parameter(s)...]
#  To use the default setting type "default"
#
#  Valid selection types and optional parameters are:
#	RouletteWheel
#	SUS
#	TournamentWOR [tournament size]
#	TournamentWR [tournament size]
#	Truncation [# copies]
#
#  When using NSGA, it can be neither SUS nor RouletteWheel.
#
TournamentWOR 2

#
# Crossover
#  Crossover probability
#  To use the default setting type "default"
#
#  Usage: Crossover type, [parameter(s)...]
#  To use the default crossover method type "default"
#  Valid crossover types and optional parameters are
#	OnePoint
#	TwoPoint
#	Uniform [genewise swap probability]
#	SBX [genewise swap probability][order of the polynomial]
#
0.9
SBX 0.5 10

#
# Mutation
#  Mutation probability
#  To use the default setting type "default"
#
#  Usage: Mutation type, [parameter(s)...]
#  Valid mutation types and the optional parameters are:
#	Selective
#	Polynomial [order of the polynomial]
#	Genewise [sigma for gene #1][sigma for gene #2]...[sigma for gene #ell]
#
0.1
Polynomial 20

#
# Scaling method
#  To use the default setting type "default"
#
#  Usage: Scaling method, [parameter(s)...]
#  Valid scaling methods and optional parameters are:
#	NoScaling
#	Ranking
#	SigmaScaling [scaling parameter]
#
NoScaling

#
# Constraint-handling method
# To use the default setting type "default"
#
# Usage: Constraint handling method, [parameters(s)...]
# Valid constraint handling methods and optional parameters are
#	NoConstraints
#	Tournament
#	Penalty [Linear|Quadratic]
#
NoConstraints

#
# Local search method
# To use the default setting type "default"
#
# Usage: localSearchMethod, [maxLocalTolerance], [maxLocalEvaluations], 
#		[initialLocalPenaltyParameter], [localUpdateParameter], 
#		[lamarckianProbability], [localSearchProbability]
#
# Valid local search methods are: NoLocalSearch and SimplexSearch
#
# For example, SimplexSearch 0.001000 20 0.500000 2.000000 0.000000 0.000000
NoLocalSearch

#
# Stopping criteria
# To use the default setting type "default"
#
# Number of stopping criterias
#
# If the number is greater than zero
#    Number of generation window
#    Stopping criterion, Criterion parameter
#
# Valid stopping criterias and the associated parameters are
#	NoOfEvaluations, Maximum number of function evaluations
#	FitnessVariance, Minimum fitness variance
#	AverageFitness, Maximum value
#	AverageObjective, Max/Min value
#	ChangeInBestFitness, Minimum change
#	ChangeInAvgFitness, Minimum change
#	ChangeInFitnessVar, Minimum change
#	ChangeInBestObjective, Minimum change
#	ChangeInAvgObjective, Minimum change
#	NoOfFronts (NSGA only), Minimum number
#	NoOfGuysInFirstFront (NSGA only), Minimum number
#	ChangeInNoOfFronts (NSGA only), Minimum change
#	BestFitness (SGA with NoNiching only), Maximum value
#
0

#
# Load the initial population from a file or not
# To use the default setting type "default"
#
# Usage: Load population (0|1)
#
# For example, if you want random initialization type 0
# On the other and if you want to load the initial population from a
# file, type
# 	1 <population file name> [0|1]
#
# Valid options for "Load population" are 0/1
# If you type "1" you must specify the name of the file to load the
# population from. The second optional parameter which indicates 
# whether to evaluate the individuals of the loaded population or not.
0

# Save the evaluated individuals to a file 
#
# To use default setting type "default".
#
# Here by default all evaluated individuals are stored and you will be
# asked for a file name later when you run the executable.
# 
# Usage: Save population (0|1)
# For example, if you don't want to save the evaluated solutions type 0
# On the other and if you want to save the evaluated solutions
# 	1 <save file name>
#
# Note that the evaluated solutions will be appended to the file.
#
# Valid options for "Save population" are 0/1
# If you type "1" you must specify the name of the file to save the
# population to.
1 evaluatedSolutions.txt