作者：李辉1,2, 张鹏1, 梁洁1,2
作者单位：1. 西南石油大学, 四川成都 610500;
2. 川庆钻探工程公司安全环保质量监督检测研究院, 四川广汉 618300
关键词：蚁群优化; 石油机械; 优化设计; 模型; 算法
摘要：
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蚁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。
Optimization of petroleum machinery based on ant colony optimization algorithm
LI Hui1,2, ZHANG Peng1, LIANG Jie1,2
1. Southwest Petroleum University, Chengdu 610500, China;
2. Safety Environment Quality Surveillance and Inspection Research Institute of Sichuan-Changqing Drilling Engineering Company, Guanghan 618300, China
Abstract: 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 petroleum machinery optimization design.
Keywords: Ant colony optimization; Petroleum machinery; Optimization design; Model; Algorithm
2009, 35(2): 96-99 收稿日期: 2008-9-5;收到修改稿日期: 2008-11-17
基金项目: 国家自然科学基金(50678154)高等学校博士点专项科研基金(20060615003)
作者简介: 李辉(1980-),男,博士研究生,主要从事蚁群算法、多学科优化设计理论及应用研究工作。
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