COMPARISON OF GENETIC ALGORITHMS AND PARTICLE SWARM OPTIMISATION FOR FERMENTATION FEED PROFILE DETERMINATION

In recent years the area of Evolutionary Computation has come into its own. Two of the popular developed approaches are Genetic Algorithms and Particle Swarm Optimisation, both of which are used in optimisation problems. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their implementation. A study is presented illustrating the performance of both genetic algorithms and particle swarm optimisation, demonstrating their ability to generate a fermentation process feed profile based on a number of objective functions. Results demonstrate how the learning mechanism developed an optimal feed profile which meets the defined criteria.