¹ Department of Automotive Engineering, Changsha Vocational & Technical College, Changsha , China
² College of Information Science and Engineering, Hunan University, Changsha, China
³ Department of Mathematics and Computer Science, University of Chizhou, Chizhou, China
⁴ Institute of Higher Education, Jinggangshan University, Ji’an, China

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Abstract—We present a chaotic hybrid invasive weed optimization (CHIWO) algorithm with an adaptive penalty function which is introduced to solve the constraints for solving the machinery optimizing problems. The proposed CHIWO algorithm runs consistently well on the studies of 13 Benchmark functions and 3 machinery optimizing problems. Experimental results indicate that CHIWO algorithm is a simple and efficient method which can improve the performance of invasive weed optimization (IWO) in terms of computing accuracy and robustness.

Index Terms—chaos, invasive weed optimization, BFGS method, hybrid algorithm, machinery optimizing

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Cite: Lijun Xie, Aijia Ouyang, Libin Liu, Minghua He, Xuyu Peng, and Xu Zhou, " Chaotic Hybrid Invasive Weed Optimization for Machinery Optimizing," Journal of Computers vol. 8, no. 8, pp. 2093-2100, 2013.