面向工程约束优化的自适应分工微粒群算法

Adaptive division particle swarm optimization for engineering constrained optimization problem

提出了一种新的算法结构,通过建立"局部环境因数"模型,利用集中式处理模式,动态分配全局勘探和局部开采子种群比例,有效地实现分工目的,平衡算法的局部和全局搜索能力。将其应用到两个不同类型的实际工程约束优化问题中进行验证,并与其他文献的改进算法进行了对比。实验结果表明,该算法比其他改进算法在计算精度、效率、鲁棒性上都有很大的提高。

A new algorithm architecture was proposed. In order to adjust effectively the ratio of exploration subgroup versus exploitation one, the algorithm adopted the centralized processing technique to construct the local environment factor, and balanced the local and global search capabilities of the algorithm. Furthermore, compared with other improved intelligent algorithms, experimental results got from the application and verification of real constrained engineering design problem indicate that the algorithm performs better in terms of accuracy, efficiency and robustness.