Solving Multi-objective Problem Of Gas Desulfuration Process Using Distributed Parallel Genetic Algorithm

In the chemical industry production, the objectives which are taken into considerations are turned from maximizing the economic benefits to simultaneously considering ecological environment, energy consumption and so on. The emergence of process simulation software provided convenient for people to simulate the actual industrial process. On the basis of the simulation, the combination of the simulation software and the evolutionary algorithms become a hot topic. However, the simulation software has shortcomings of high model complexity and weak convergence. These shortcomings lead to high time using and low optimizing efficiency. In the field of engineering and scientific research, the method of parallel computing can improve convergence and reduce computation. The characteristics of parallel algorithms provided an efficient and feasible solutions for people to solve chemical multi-objective optimization problem.Based on consideration of the above problems, this paper are studied the multi-objective optimization algorithms and parallel computing techniques. The distributed parallel genetic algorithm are put forward from the combination of parallel algorithms and process simulator. The method can effectively solve the process simulation and optimization software with optimization problems. Also, this method is applied to the optimization of gas desulfurization and recovery system. This study included the following elements:(1) Learned and summarized the excellent algorithms in recent decades, chose non-dominated sorting genetic algorithm with elitist strategy as the researching object, and researched its parallel portion.(2) Considered the fitness evaluation section to parallel computing of NSGA-II by selecting a master-slave model, populations distributed parallel genetic algorithm, and used it to solve a example of solvent regeneration towel. It can effectively improve the efficiency and reduce the time consumption.(3) Selected the appropriate absorber for industrial processes and researched the solvent regeneration refinery desulfurization. The solvent regeneration improvement programs are focused on the whole process of simulation. By adjusting the solvent concentration, the regeneration tower reflux ratio and other variables, the whole process can be optimized among using PDPGA.(4) Summarized the work of this paper systematically, and prospected the research following-up.