针对石油机械设计中传统优化方法解决大规模复杂优化问题存在的局限性,提出了基于蚁群优化算法(ACO)的石油机械优化设计方法。在介绍蚁群优化算法的原理、基本框架和模型的基础上,通过具体的算例,证明ACO计算效率高,寻优能力强,模型本身的全局优化、较强鲁棒性和并行性使得蚊群算法适合于大规模的复杂优化问题,在石油机械优化设计中具有较好的应用前景。
In order to overcome the limitations of the traditional petroleum machinery optimization methods, an improved optimization design based on ant colony optimization (ACO) algorithm is brought forward. It is suitable for solving complex optimization problems because of its global optimization, stronger robustness and concurrent properties. ACO is applied in optimization of a concrete mechanical design based on the introduction of the principle, the frame of algorithm and the mathematical model of ACO. The result shows its efficiency is high, and it has good application prospect in petrohum machinery optimization design.