Evolutionary and genetic algorithms applied to hot rolling: A multi-objective rolling schedule studied using particle swarm algorithm


A scheduling problem pertaining to the hot rolling plant of an integrated steel plant is addressed using a multiobjective optimization approach. A Particle Swarm Algorithm that mimics the flight of a flock of birds or a school of fish is used to generate the Pareto fronts representing the best possible compromises between some conflicting objectives. The increasing importance of the research based upon Evolutionary and Genetic Algorithms is also highlighted.