Cleaner production for continuous digester processes based on hybrid Pareto genetic algorithm

Article type: Research Article

Authors: Jin, Fu-jiang | Wang, Hui | Li, Ping

Affiliations: Institute of Industrial Process Control, Zhejiang University, Hangzhou 310027, China

Abstract: Pulping production process produce large amount of wastewater and pollutant emitted, which has become one of the main pollution sources in pulp and paper industry. To solve this problem, it is necessary to implement cleaner production by using modeling and optimization technology. This paper studies the model and multi-objective genetic algorithms for continuous digester process. A model is established, in which environmental pollution and saving energy factors are considered. A hybrid genetic algorithm based on Pareto stratum-niche count is designed for finding near-Pareto or Pareto optimal solutions in the problem. A new genetic evaluation and selection mechanism is proposed. Using the real data from a pulp mill shows the results of computer simulation. Through comparing with the practical curve of digester, this method can reduce the pollutant effectively and increase the profit while keeping the pulp quality constant.

Keywords: cleaner production, multi-objective optimization, genetic algorithm, Pareto stratum, concentration of residual alkali, Kamyr continuous digester

Journal: Journal of Environmental Sciences, vol. 15, no. 1, pp. 129-135, 2003