Study On Algorithms Of Intelligentized Global Optimization And Application In The Synthesis Of Process System Engineering

Process system synthesis and analysis are one of the most important parts of process system engineering (PSE). Constraints, which are non-linear or from logical strategy and experience, make it difficult to obtain the global optimization of process synthesis and analysis.Because of the complexity of nonlinear programming (NLP) / Mixed Integer Nonlinear Programming (MINLP), and the lack of effective mathematics algorithms for large scale NLP/MINLP, the optimization algorithms to process synthesis are still considered the most difficult.The main contents of this dissertation are below:1) Information extraction technique has been introduced to improve genetic algorithms. It was pointed out that population and the individuals of a population are information points, which represents the useful information about the available space. With parameter matrix of mutation and parameter matrix of crossover, generalizing from information extraction and population could be mutated and crossovered on the whole. Genetic algorithms could be considered as a combination operation, which is stochastic and entire.Parallel and adaptive strategy enhanced the ergodic ability of the algorithm to available space, and crossover overcame effectively the information lose resulted from "Genetic Drift".The solutions to multiple-peak and rigid functions, or to NLP / MINLP problems such as process design and synthesize of reactor network, show us the efficiency of this improvement. Especially, to some problems, the results are rather more satisfied.2) The synthesis of heat exchanger networks (HENs) is a problem of a bipartite graph, whose heart to constructing open and close Hamilton circles between cold and hot streams. On the other hand, it could be considered as searching the shortest bipartite match loop among cold and hot streams.In this dissertation, a loop identification strategy to base loop in HENs is put...