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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。
In order to solve the problem of Mixed Integer Non-Linear Programming (MINLP) in process synthesis, the improved Particle Swarm Optimization (PSO) algorithm is used to solve the problem. Based on the basic PSO algorithm, the PSO algorithm is applied to solve the MINLP problem by using the penalty function and the sigmoid function. The PSO algorithm is tested by using two test functions and a process comprehensive example and compared with other algorithms The results are compared. The results show that the PSO algorithm outperforms the general algorithm in terms of the universality and the accuracy of the solution. It is an effective method to solve the MINLP problem.