Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review

@article{Bonyadi2017ParticleSO,
  title={Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review},
  author={Mohammad Reza Bonyadi and Zbigniew Michalewicz},
  journal={Evolutionary Computation},
  year={2017},
  volume={25},
  pages={1-54}
}
This paper reviews recent studies on the Particle Swarm Optimization (PSO) algorithm. The review has been focused on high impact recent articles that have analyzed and/or modified PSO algorithms. This paper also presents some potential areas for future study. 
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364 Citations
Highly Influential Citations
17
Background Citations
84
Methods Citations
58
Results Citations
1

364 Citations

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Citation Type

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This paper focus on a complex problem of job shop scheduling where each jobs have a multiple possible operations sequences and a new algorithm based on Particle Swarm Optimization Global Velocity (PSOVG) was proposed to solve this.
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The conclusions suggest that the original PSO has changed to avoid its own disadvantages as premature convergence and also that some methods related to the inertia weight, constriction factor, additional operators, or hybridization with other metahuristics have been applied to improve the results in complex problems.
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The benchmarking functions are used to evaluate and check the particle swarm optimization (PSO) algorithm and it is compared with genetic algorithm (GA) in order to prove capability of PSO.
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An analysis using some recent categorizations for exploitation and exploration, and especially the effects of selection, sheds light on how MPS performs better in high dimensions than popular metaheuristics such as Differential Evolution and Particle Swarm Optimization.
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TLDR
This work focuses on reviewing a heuristic global optimization method called particle swarm optimization (PSO), the mathematical representation of PSO in contentious and binary spaces, the evolution and modifications ofPSO over the last two decades and a comprehensive taxonomy of heuristic-based optimization algorithms.
On the Particle Swarm Optimization Control Using Analytic Programming and Self Organizing Migrating Algorithm
TLDR
This article looks at the feedback control of system which contains randomness from the time delay feedback control perspective, and selected particles are controlled to a stable point by adding small perturbations to the particle position.
Hybrid PSO Algorithm with Iterated Local Search Operator for Equality Constraints Problems
TLDR
A hybrid PSO algorithm with an ILS (Iterated Local Search) operator for handling equality constraints problems in mono-objective optimization problems and shows improvement in accuracy, reducing the gap for the tested problems.
Convergence analysis of particle swarm optimization using stochastic Lyapunov functions and quantifier elimination
TLDR
This paper presents a computational procedure and shows that this approach leads to reevaluation and extension of previously know stability regions for PSO using a Lyapunov approach under stagnation assumptions.
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