The Economic Optimization of Pulp and Paper Making Processes Using Computational Intelligence

In this paper we present an application of two Computational Intelligence Algorithms, namely Particle Swarm Optimization (PSO) Algorithm and Differential Evolution (DE) for finding and optimal solution to two optimization problems that occur in a paper industry. The first problem deals with the economic optimization of a hypothetical but realistic Kraft pulping process and in the second problem we have considered the optimization of Boiler load allocation problem. Both the problems form an integral part of paper making process. The simulation results show the efficiency and time effectiveness of DE and PSO.