ALPSO - Augmented Lagrangian Particle Swarm Optimizer

This is a parallel augmented Lagrange multiplier particle swarm optimizer developed in Python. It solves nonlinear non-smooth constrained problems using an augmented Lagrange multiplier approach to handle constraints. [Jansen2011] [LICENSE]

class pyALPSO.ALPSO(pll_type=None, *args, **kwargs)

Bases: pyOpt.pyOpt_optimizer.Optimizer

ALPSO Optimizer Class - Inherited from Optimizer Abstract Class

ALPSO Optimizer Class Initialization

Keyword arguments:

• pll_type -> STR: ALPSO Parallel Implementation (None, SPM- Static, DPM- Dynamic, POA-Parallel Analysis), Default = None

Documentation last updated: February. 2, 2011 - Ruben E. Perez

__solve__(opt_problem={}, store_sol=True, disp_opts=False, xstart=[], 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
• xstart -> : , Default = []
• 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. 2, 2011 - Ruben E. Perez

Optimizer Options

Name	Type	Default Value	Notes
SwarmSize	int	40	Number of Particles (Depends on Problem dimensions)
maxOuterIter	int	200	Maximum Number of Outer Loop Iterations (Major Iterations)
maxInnerIter	int	6	Maximum Number of Inner Loop Iterations (Minor Iterations)
minInnerIter	int	6	Minimum Number of Inner Loop Iterations (Minor Iterations)
dynInnerIter	int	0	Dynamic Number of Inner Iterations Flag
stopCriteria	int	1	Stopping Criteria Flag (0 - maxIters, 1 - convergence)
stopIters	int	5	Consecutively Number of Iterations for Convergence
etol	float	1e-3	Absolute Tolerance for Equality constraints
itol	float	1e-3	Absolute Tolerance for Inequality constraints
rtol	float	1e-2	Relative Tolerance for Lagrange Multipliers
atol	float	1e-2	Absolute Tolerance for Lagrange Function
dtol	float	1e-1	Relative Tolerance in Particles Distance to Terminate (GCPSO)
printOuterIters	int	0	Number of Iterations Before Print Outer Loop Information
printInnerIters	int	0	Number of Iterations Before Print Inner Loop Information
rinit	float	1.0	Initial Penalty Factor
xinit	int	0	Initial Position Flag (0 - no position, 1 - position given)
vinit	float	1.0	Initial Velocity of Particles Normalized in [-1,1] Space
vmax	float	2.0	Maximum Velocity of Particles Normalized in [-1,1] Space
c1	float	2.0	Cognitive Parameter
c2	float	1.0	Social Parameter
w1	float	0.99	Initial Inertia Weight
w2	float	0.55	Final Inertia Weight
ns	int	15	Consecutive Successes Before Radius will be Increased (GCPSO)
nf	int	5	Consecutive Failures Before Radius will be Increased (GCPSO)
dt	float	1	Time step
vcrazy	float	1e-4	Craziness Velocity
fileout	int	1	Flag to Turn On Output to filename
filename	str	‘ALPSO.out’	Output File Name
seed	float	0	Random Number Seed (0 - Auto-Seed based on time clock)
HoodSize	int	40	Number of Neighbours of Each Particle
HoodModel	str	‘gbest’	Neighbourhood Model (dl/slring, wheel, Spatial, sfrac
HoodSelf	int	1	Selfless Neighbourhood Model
Scaling	int	1	Design Variables Scaling (0- no scaling, 1- scaling [-1,1])