NSGA2 - Non Sorting Genetic Algorithm II

This optimizer is a non-dominating sorting genetic algorithm that solves non-convex and non-smooth single and multiobjective optimization problems. The algorithm attempts to perform global optimization, while enforcing constraints using a tournament selection-based strategy. [Deb2002] [LICENSE]

class pyNSGA2.NSGA2(pll_type=None, *args, **kwargs)

Bases: pyOpt.pyOpt_optimizer.Optimizer

NSGA2 Optimizer Class - Inherited from Optimizer Abstract Class

NSGA2 Optimizer Class Initialization

Keyword arguments:

• pll_type -> STR: Parallel Implementation (None, ‘POA’-Parallel Objective Analysis), Default = None

Documentation last updated: Feb. 16, 2010 - Peter W. Jansen

__solve__(opt_problem={}, store_sol=True, disp_opts=False, store_hst=False, hot_start=False, *args, **kwargs)

Run Optimizer (Optimize Routine)

Keyword arguments:

• opt_problem -> INST: Optimization instance
• store_sol -> BOOL: Store solution in Optimization class flag, Default = True
• disp_opts -> BOOL: Flag to display options in solution text, Default = False
• store_hst -> BOOL/STR: Flag/filename to store optimization history, Default = False
• hot_start -> BOOL/STR: Flag/filename to read optimization history, Default = False

Additional arguments and keyword arguments are passed to the objective function call.

Documentation last updated: February. 16, 2011 - Peter W. Jansen

Optimizer Options

Name	Type	Default Value	Notes
PopSize	int	100	Population Size (a Multiple of 4)
maxGen	int	150	Maximum Number of Generations
pCross_real	float	0.6	Probability of Crossover of Real Variable (0.6-1.0)
pMut_real	float	0.2	Probablity of Mutation of Real Variables (1/nreal)
eta_c	float	10.0	Distribution Index for Crossover (5-20) must be > 0
eta_m	float	20.0	Distribution Index for Mutation (5-50) must be > 0
pCross_bin	float	0.0	Probability of Crossover of Binary Variable (0.6-1.0)
pMut_real	float	0.0	Probability of Mutation of Binary Variables (1/nbits)
PrintOut	int	1	Flag to Turn On Output to files (0-None, 1-Subset, 2-All)
seed	float	0.0	Random Number Seed (0 - Auto-Seed based on time clock)