An Adaptive Invasive Weed Optimization Algorithm

作者：Peng, Shuo; Ouyang, A. -J.^*; Zhang, Jeff Jun

来源：International Journal of Pattern Recognition and Artificial Intelligence, 2015, 29(2): 1559004.

DOI：10.1142/S0218001415590041

• Adaptation
• global optimization
• invasive weed optimization
• step size

With regards to the low search accuracy of the basic invasive weed optimization algorithm which is easy to get into local extremum, this paper proposes an adaptive invasive weed optimization (AIWO) algorithm. The algorithm sets the initial step size and the final step size as the adaptive step size to guide the global search of the algorithm, and it is applied to 20 famous benchmark functions for a test, the results of which show that the AIWO algorithm owns better global optimization search capacity, faster convergence speed and higher computation accuracy compared with other advanced algorithms.

• 出版日期2015-3
• 单位井冈山大学