期刊
IEEE TRANSACTIONS ON CYBERNETICS
卷 48, 期 3, 页码 848-861出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2017.2657797
关键词
Clonal selection algorithm (CSA); complex engineering optimization (CEO); degeneration recognizing (DR); multimodal optimization; wet spinning coagulating process
类别
资金
- Key Project of the National Natural Science Foundation of China [61134009]
- National Natural Science Foundation of China [61473077, 61473078, 61503075]
- National Natural Science Funds Overseas and Hong Kong and Macao Scholars [61428302]
- National Key Research and Development Plan from Ministry of Science and Technology [2016YFB0302701]
- International Collaborative Project of the Shanghai Committee of Science and Technology [16510711100]
- Program for Changjiang Scholars from the Ministry of Education
In this paper, a computing speed improvement for the clonal selection algorithm (CSA) is proposed based on a degeneration recognizing (DR) method. The degeneration recognizing clonal selection algorithm (DR-CSA) is designed for solving complex engineering multimodal optimization problems. On each iteration of CSA, there is a large amount of eliminated solutions which are usually neglected. But these solutions do contain the knowledge of the nonoptimal area. By storing and utilizing these data, the DR-CSA is aimed to identify part of the new population as degenerated and eliminate them before the evaluation operation, so that a number of evaluation times can be avoided. This pre-elimination operation is able to save computing time because the evaluation is the main reason for the time cost in the complex engineering optimization problem. Experiments on both test function and a real-world engineering optimization problem (wet spinning coagulating process) are conducted. The results show that the proposed DR-CSA is as accurate as regular CSA and is effective in reducing a considerable amount of computing time.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据