Study On The Genetic Algorithm Uses In Multi-Objecticve Process Optimization Comprehensive

The process system synthesis is refers that seek system structure and its various subsystems capability according to the system characteristic, and causes the system to carry on the optimized combination according to the stipulation goal. It is the process system engineering core content, is the key of process system design. Because in the process integration design needed to consider the environment, the efficiency and the maneuverability simultaneously, the chemical process multi-objectives optimization synthesizes become an important research topic. This question almost solves the model of Multi-objectives Mix-integer Nonlinear Programming (MOMINLP). The multi-objectives optimization is different from the simple objective optimize, there is few absolute optimal solution to multi-objectives problem, but has the set of non-dominated solutions which called Pareto-optimal front. The multi-objectives optimization technology main goal is seek one or manysatisfactory solutions in the Pareto-optimal front. The solution methods mainly have mathematics programming and the multi-objectives evolution algorithms. The Multi-objectives Genetic Algorithms (MOGA) as representative evolution algorithms was considered specially suit to solve this kind of questions. The genetic algorithms mostly use in the single objective questions optimization, in recent years the research that apply the Genetic Algorithms to the multi-objectives optimized has been developed.This article based on the fully studying in the multi-objective optimization method, has developed a multi-objective chemical process optimization synthesis system on the platform of the chemical industry general simulation software ECSS. This system uses the Genetic Algorithm.This system has made the improvement to Non-dominated Sorting Genetic Algorithms â…¡ (NSGA-â…¡). In view of the characteristics of chemical process model, discuss applied research of the improved Non-dominated Sorting Genetic Algorithms II (NSGA-II) in the process synthesis. And considers that t the improved Non-dominated Sorting Genetic Algorithms is the effective algorithms to solve this kind of questions.This article developed the module which had the multi-objective optimization synthesis function. This module integer to the chemical industry simulation software ECSS, provided the convenience but reliable platform for the process optimization synthesis, realized process optimization synthesis function to process simulation software, satisfied the user' s demands to the chemical process multi-objectives optimization synthesis.Example indicated that this system can be satisfied the...