【摘 要】
：
Dynamic multi-objective optimization is a complex and difficult research topic of process systems engineering.In this paper,a modified Bare-bones MOPSO algo
【机 构】
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East China University of Science and Technology,China
【出 处】
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第三届先进计算智能与智能信息学国际研讨会(The Third International Workshop on Adv
论文部分内容阅读
Dynamic multi-objective optimization is a complex and difficult research topic of process systems engineering.In this paper,a modified Bare-bones MOPSO algorithm is proposed that takes advantage of few parameters of bare-bones algorithm.To avoid premature convergence,Gaussian mutation is introduced; and an adaptive sampling distribution strategy is also used to improve the exploratory capability.Moreover,a circular crowded sorting approach is adopted to improve the uniformity of the population distribution.Finally,by combining the algorithm with control vector parameterization,an approach is proposed to solve the dynamic optimization problems of chemical processes.It is proved that the new algorithm performs better compared with other classic multi-objective optimization algorithms through the results of solving three dynamic optimization problems.
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