The Particle Swarm Optimization's Amelioration Of Transacting Multi-objective Optimization Problem And Its Application

Engineering design problems generally involve several design objectives. Among These related objective , It's potentially conflicting in nature. Multidisciplinary Design Optimization(MDO) has grown to the point of gaining near universal recognition in its ability to lead to better designs,both in the areas of academic research and pratical application. At the heart of MDO problem is a multi-objective optimization problem. Therefore, it is really valuable to research multi-objective optimization theory and technologies.This research focuses on synthesizing multi-objective optimization with Pareto Particle Swarm Optimization(PSO) and chaos optimization to develop two more effective multi-objective optimization methods and one trying application: first developed an effective hybrid PSO based on two-chaos optimization, which could deal with selection of fitness value of multi-objective function,avoiding blindness search in the research space and it is propitious to arithmetic evolve towards the best answer of Pareto; next developed an effective hybrid PSO based on harmonious model of muiti-objective decision-making, which could conquer the defect : the scale-limited Particle Swarm difficultily process Pareto comositor's compartion in the high-dimension space among them or all the individual have the best answer of Pareto ,at last no measure processes naturally selection of next individual. The modified arithmetic is applicable and effective in the scale complex engineering multi-objective optimization problems; providing a more effective solution for the big scale mutil-objective optimization problems. thirdly, we try to solve the optimal design of the oil-gas gathering network parameter by using particle swarm optimization.then solve an actual example by using particle swarm optimization with double -chaos optimization.Numerical results show that this algrithm is feasible and can get more precise results than other methods .PSO is a rising optimization tool,which could reduce calculative burthen for big scale mutil-objective optimization problems and deal with it, it get more perfect better answer of Pareto and expediently actual apply. the results of test show that the hybrid particle swarm optimaziton is effective and correct.