Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Introduction to Discrete Event Systems
Introduction to Discrete Event Systems
Knowledge and Information Systems
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
Integral Particle Swarm Optimization with Dispersed Accelerator Information
Fundamenta Informaticae - Swarm Intelligence
Boid particle swarm optimisation
International Journal of Innovative Computing and Applications
Individual predicted integral-controlled particle swarm optimisation
International Journal of Innovative Computing and Applications
Nearest neighbor interaction PSO based on small-world model
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
International Journal of Bio-Inspired Computation
A new stochastic algorithm to direct orbits of chaotic systems
International Journal of Computer Applications in Technology
Cooperative game-based routing approach for wireless sensor network
International Journal of Computer Applications in Technology
Particle swarm optimisation-based support vector machine for intelligent fault diagnosis
International Journal of Computer Applications in Technology
Integral Particle Swarm Optimization with Dispersed Accelerator Information
Fundamenta Informaticae - Swarm Intelligence
Bio-inspired computation: success and challenges of IJBIC
International Journal of Bio-Inspired Computation
Hi-index | 0.00 |
The computation of optimal control variables for a two-stage steel annealing process which comprises of one or more furnaces is proposed in this paper. The heating and soaking furnaces of the steel annealing line form the two-stage hybrid systems. Three algorithms including particle swarm optimisation (PSO) with globally and locally tuned parameters (GLBest PSO), a parameter free PSO algorithm (pf-PSO) and a PSO-like algorithm via extrapolated PSO (ePSO) are considered to solve this optimal control problem for the two-stage steel annealing processes (SAP). The optimal solutions including optimal line speed, optimal cost and job completion time obtained through these three methods are compared with one another and those obtained via conventional PSO (cPSO) with time varying inertia weight (TVIW) and time varying acceleration coefficient (TVAC). From the results obtained through the five algorithms considered, the efficacy and validity of each algorithm are analysed.