Applicability of the fuzzy operators in the design of fuzzy logic controllers
Fuzzy Sets and Systems
Swarm intelligence
Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
Recent approaches to global optimization problems through Particle Swarm Optimization
Natural Computing: an international journal
Analysis of static simulated annealing algorithms
Journal of Optimization Theory and Applications
Comparison between Genetic Algorithms and Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
The particle swarm optimization algorithm: convergence analysis and parameter selection
Information Processing Letters
Solving Unit Commitment Problem Using Hybrid Particle Swarm Optimization
Journal of Heuristics
Particle swarm based Data Mining Algorithms for classification tasks
Parallel Computing - Special issue: Parallel and nature-inspired computational paradigms and applications
Mathematics and Computers in Simulation
A Study of Global Optimization Using Particle Swarms
Journal of Global Optimization
A fuzzy-based lifetime extension of genetic algorithms
Fuzzy Sets and Systems
Pattern Recognition Letters
Registration of 3d range images using particle swarm optimization
ASIAN'04 Proceedings of the 9th Asian Computing Science conference on Advances in Computer Science: dedicated to Jean-Louis Lassez on the Occasion of His 5th Cycle Birthday
Parameter control in evolutionary algorithms
IEEE Transactions on Evolutionary Computation
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
On the computation of all global minimizers through particle swarm optimization
IEEE Transactions on Evolutionary Computation
Implementation of evolutionary fuzzy systems
IEEE Transactions on Fuzzy Systems
Integral Particle Swarm Optimization with Dispersed Accelerator Information
Fundamenta Informaticae - Swarm Intelligence
Multi-agent simulated annealing algorithm based on particle swarm optimisation algorithm
International Journal of Computer Applications in Technology
Integral Particle Swarm Optimization with Dispersed Accelerator Information
Fundamenta Informaticae - Swarm Intelligence
International Journal of Innovative Computing and Applications
A fuzzified systematic adjustment of the robotic Darwinian PSO
Robotics and Autonomous Systems
Particle swarm classification: A survey and positioning
Pattern Recognition
Sensor deployment for fault diagnosis using a new discrete optimization algorithm
Applied Soft Computing
Gases Brownian Motion Optimization: an Algorithm for Optimization (GBMO)
Applied Soft Computing
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Particle Swarm Optimisation (PSO) algorithm is a stochastic search technique, which has exhibited good performance across a wide range of applications. However, very often for multimodal problems involving high dimensions, the algorithm tends to suffer from premature convergence. Analysis of the behaviour of the particle swarm model reveals that such premature convergence is mainly due to the decrease of velocity of particles in the search space that leads to a total implosion and ultimately fitness stagnation of the swarm. This paper introduces Turbulence in the Particle Swarm Optimisation (TPSO) algorithm to overcome the problem of stagnation. The algorithm uses a minimum velocity threshold to control the velocity of particles. The parameter, minimum velocity threshold of the particles is tuned adaptively by a fuzzy logic controller embedded in the TPSO algorithm, which is further called as Fuzzy Adaptive TPSO (FATPSO). We evaluated the performance of FATPSO and compared it with the Standard PSO (SPSO), Genetic Algorithm (GA) and Simulated Annealing (SA). The comparison was performed on a suite of 10 widely used benchmark problems for 30 and 100 dimensions. Empirical results illustrate that the FATPSO could prevent premature convergence very effectively and it clearly outperforms SPSO and GA.