Particle swarm optimisation: a triggered approach
Mohamed H. Gadallah, Mohamed B. Ali, Ahmed Mohamed Emam · International Journal of Industrial and Systems Engineering · 2013
This paper presents a modification to the particle swarm optimisation (PSO) to tackle two difficulties observed in many applications: premature convergence of the solution, and the degree of confidence of the decision maker. This approach, known as triggered particle swarm optimisation, treats the problem in a dynamic environment and making each particle reset its record of best positions. This approach treated the PSO by triggering the particle swarm optimiser in a dynamic environment, making each particle reset its record of its best position. This, in turn, avoids making position and velocity changes based on outdated information. Due to random-based nature, a statistical confidence interval estimation approach is developed around the returned optimum at different levels. The proposed algorithm, triggered particle swarm optimisation (T-PSO), performs significantly better than the original PSO and the new particle swarm optimisation (NPSO) discussed in references.