Multi-objective Optimization For Batch Processes Design With Environmental Impact Consideration

With the development of chemical and processing industry, pollution problem has attracted increasing concern in the global scope for its impact on the environment and human health. It must be emphasized that the design of batch plants has been for long been identified as a key problem in chemical engineering. In order to keep competition in market, multi-objective optimal design of batch process with minimization of investment and environmental impact has always been one of the researching focuses. It also brings the dual benefit of economy and environment.Multi-objective optimal design of batch process with minimization of investment and environmental impact has been addressed as a mono-objective optimization with a weight factor on the environmental term. But there is no easy way to get a right value for the weight factor. It is necessary to solve the problem and give a group of solutions, so that the designer can have more alternatives to make decisions. In the present paper, we change mono-objective model to multi-objective model which were developed by Yao Zhao-Ling. The problem is solved with a multi-objective genetic algorithm (GA) optimization method combined with linear programming (LP). GA is used to solve the master program problem and LP is used to solve sub-problems. The GA/LP algorithm takes advantage of GA method as well as LP method which can solve problems with continuous variables and a large amount of constraint equations. A group of Pareto solutions are provided. The results are compared with those of mono-objective optimization with a weight factor on the environmental term. The proposed method is shown to be effective for solving the addressed multi-objective optimization problems, and the results provide more alternatives for decision-making for batch plant design with the consideration of environmental impact.