【摘要】 考虑到普通串行遗传算法处理结构动力优化问题时效率不高,引入并行遗传算法进行求解以提高效率,提出了一种新的自适应迁移算子,将其与串行遗传算法的自适应交叉,以及变异算子相结合,在4台微机组成的COW集群上实现了双向链式自适应迁移粗粒度并行遗传算法。同时为更加准确的描述实际工程问题,建立了结构模糊优化模型,提出了模糊水平截集因子的遗传编码确定方法,方便了模糊优化模型的求解。在最后给出的两个算例中,显示了自适应并行遗传算法的高效性以及模糊优化模型较之普通优化模型的合理性和有效性。更多还原

【Abstract】 See to the fact that normal serial genetic algorithm handling dynamic optimization problem is not efficient enough,parallel genetic algorithm is suggested to solve this problem,and a new adaptive migration operator is proposed.Combining this adaptive migration operator with adaptive crossover operator and mutation operator of serial genetic algorithm,the adaptive bi-oriented migration coarse-grained parallel genetic algorithm which uses ring topology is implemented within a 4-processor COW environment.The fuzzy model of normal dynamic optimization is established for describing the real engineering problems more practicaly,the genetic coding method of calculating the optimal fuzzy level value λ* is presented,which can solve fuzzy model more conveniently.The two examples of the last are given to demonstrate the efficiency of the adaptive parallel genetic algorithm and certificated that the fuzzy optimization model is better than the normal optimization model,which is more practical and effective.更多还原