Study On The Multi-Objective Genetic Algorithm Used In Process Synthesis In Modular Simulator Environment

With the development of the computer technique and the chemical synthesis engineering, many mathematical models of various units and commercial software have been developed. But because of the complexity and concretes of the chemical process, simulated software is impossible to satisfy all the demand of the actual process, so the union of many software is enough to resolve a problem of synthesis process. The importance of software integration was appeared to avoid the programming of software function repeatedly and realize the union of the software function.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 and the key of process system design. Multi-objective optimization has become an important research topic of the chemical process synthesizes with people's attention of environment and resources. Solution strategies of multi-objective optimization synthesis mainly have mathematic programming method and multi-objective evolution algorithms. The genetic algorithms for the representative of evolution algorithms is build up the foundation on evolution of the living .It is random algorithms by means of the nature choice and encourages of genetic populations. Because the genetic algorithm can handle a possible solution at the same time, and pass to operate once and then can find out a not inferior solve. Genetic algorithm is free from some conditional restrict such as Pareto curved shape, the target number etc. Moreover it can also handle to the problem of random and the uncertain manhunt space .This is exactly a problem of mathematic programming...