Standard Particle Swarm Optimisation 2011 at CEC-2013: A baseline for future PSO improvements

@article{ZambranoBigiarini2013StandardPS,
  title={Standard Particle Swarm Optimisation 2011 at CEC-2013: A baseline for future PSO improvements},
  author={Mauricio Zambrano-Bigiarini and Maurice Clerc and Rodrigo Rojas-Mujica},
  journal={2013 IEEE Congress on Evolutionary Computation},
  year={2013},
  pages={2337-2344}
}
In this work we benchmark, for the first time, the latest Standard Particle Swarm Optimisation algorithm (SPSO-2011) against the 28 test functions designed for the Special Session on Real-Parameter Single Objective Optimisation at CEC-2013. [] Key Result This work is the first effort towards providing a baseline for a fair comparison of future PSO improvements.

Figures and Tables from this paper

An improved rotationally invariant PSO: A modified standard PSO-2011
TLDR
It is clarified that SPSO2011 performance is affected by the distribution of the center of the search range, and a novel update rule is proposed to improve the global search ability.
A Modified Standard PSO-2011 with Robust Search Ability
TLDR
A modified diversity-guided SPSO (DGAP-MSPSO) algorithm is proposed to reinforce diversity-maintain ability as well as improve local search ability in Standard particle swarm optimization (SPSO2011).
Genetic mechanism-enhanced standard particle swarm optimization 2011
TLDR
This study attempts to enhance the exploration ability of SPSO2011 further by conditionally introducing a new genetic mechanism to improve the personal best condition of each particle.
Enhanced Particle Swarm Optimization Algorithm: Efficient Training of ReaxFF Reactive Force Fields.
TLDR
A significant improvement in the search quality and efficiency on multimodal functions can be achieved by enhancing the basic rotation-invariant PSO algorithm with isotropic Gaussian mutation operators.
Particle swarm optimization with neighborhood-based budget allocation
TLDR
A new variant of PSO where each particle is dynamically assigned different computational budget based on the quality of its neighborhood is proposed to favor particles with high-quality neighborhoods by asynchronously providing them with more function evaluations than the rest.
A Framework for Constrained Optimization Problems Based on a Modified Particle Swarm Optimization
TLDR
A modified PSO algorithm is proposed by adding a newly developed self-adaptive strategy to the standard particle swarm optimization 2011 (SPSO 2011) algorithm to solve COPs, and the adaptive relaxation method is applied to handle constraints of COPs and evaluate candidate solutions in the developed framework.
Comparison of PSO variants applied to large scale optimization problems
TLDR
Analysis and experimental analysis suggest that CCPSO2 and OBL-PSO seem to be highly competitive optimization algorithms to solve large-scale complex and multimodal optimization problems.
Particle swarm variants: standardized convergence analysis
TLDR
It was found that using a specially designed objective function for convergence analysis is both a simple and valid method for performing assumption free convergence analysis.
A new self-adaptive PSO based on the identification of planar regions
In this paper, we propose a new approach for self-adaptive particle swarm optimization, using the function's topology to adapt the parameters and modifying them when a planar region is identified in
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 36 REFERENCES
On the improvements of the particle swarm optimization algorithm
Standard Particle Swarm Optimisation
TLDR
Since 2006, three successive standard PSO versions have been put on line on the Particle Swarm Central, namely SPSO 2006, 2007, and 2011, and the basic principles of all three versions can be informally described the same way.
A method to improve Standard PSO
TLDR
This report presents a personal method to design a more accurate version of PSO, assuming the authors know what kind of problems they will have to solve, and explains why the classical "mean best" performance criterion may easily be completely meaningless.
Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization
TLDR
This special session is devoted to the approaches, algorithms and techniques for solving real parameter single objective optimization without making use of the exact equations of the test functions.
A model-independent Particle Swarm Optimisation software for model calibration
A modified particle swarm optimizer
  • Y. Shi, R. Eberhart
  • Computer Science
    1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360)
  • 1998
TLDR
A new parameter, called inertia weight, is introduced into the original particle swarm optimizer, which resembles a school of flying birds since it adjusts its flying according to its own flying experience and its companions' flying experience.
Biases in Particle Swarm Optimization
TLDR
The authors create fitness functions that are easy or hard for PSO to solve, depending on the rotation of the function, by showing that the rotational variance is related to the concentration along lines parallel to the coordinate axes.
Beyond Standard Particle Swarm Optimisation
  • M. Clerc
  • Physics
    Int. J. Swarm Intell. Res.
  • 2010
TLDR
The author goes beyond simple merging by suggesting simple yet robust changes and solving a few well-known, common problems, while retaining the classical structure of PSO.
Comparing inertia weights and constriction factors in particle swarm optimization
  • R. Eberhart, Y. Shi
  • Computer Science
    Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)
  • 2000
TLDR
It is concluded that the best approach is to use the constriction factor while limiting the maximum velocity Vmax to the dynamic range of the variable Xmax on each dimension.
Particle swarm optimization
TLDR
A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
...
1
2
3
4
...