HomeDLSU Engineering Journalvol. 18 no. 1 (2006)

Development of Pollution Prevention Strategies Using Swarm Intelligence

Raymond R. Tan

Discipline: Engineering, Technology



Particle swarm optimization (PSO) is a metaheuristic algorithm based on the behavior of social animals. Its key advantages are its computational efficiency and ability to locate global optima by incorporating "stochastic kicks." Use of a discretized PSO in selecting an optimal array of pollution prevention techniques for day brick production is described. Statistically significant improvement in the rate of successful convergence was achieved by modifying the basic PSO algorithm.