改进的微粒群优化算法在过程综合中的应用

针对过程综合中的混合整数非线性规划(Mixed Integer Non-Linear Programming，MINLP)问题，利用改进的微粒群优化(Particle Swarm Optimization，PSO)算法对其进行求解。在基本的PSO算法的基础上，通过利用罚函数和引入sigmoid函数把PSO算法应用到MINLP问题的求解中，利用两个测试函数和一个过程综合的实例对其进行了测试并与其它算法所得的结果进行了比较，结果表明，PSO算法在使用的普遍性、求解的准确性方面都优于一般的算法，是一种有效的求解MINLP问题的方法。

Applying particle swarm optimization in process synthesis

Process synthesis problems can be mathematically represented as mixed-integer nonlinear programming(MINLP)models,which are often irregular,large and non-convex and difficult to get the overall optimum by traditional methods.In this paper,a modi-fied particle swarm optimization(PSO)is used to solve MINLP problems.By introducing penalty function and used sigmoid function,the PSO algorithm,which originally can only used in continous variables with max/min limitations,can be used to solve MINLP prob-lems with equations and inequalities constraints.Examples are used to demonstrate the validity of the method and the results are com-pared with the results obtained by other methods to show the validity and efficiency of the modified PSO algorithm.