caa a22 4500 605469237 CHVBK 20210128100321.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s00500-015-1896-x doi (NATIONALLICENCE)springer-10.1007/s00500-015-1896-x A hybrid version of invasive weed optimization with quadratic approximation [Elektronische Daten] [Y. Naidu, A. Ojha] Invasive weed optimization (IWO) is a recent meta-heuristic optimization technique, based on the life cycle of plants. It has been applied in many engineering applications as well as in real world problems. In this paper, a hybrid version of IWO with the quadratic approximation (QA) operator, referred as QAIWO, has been investigated to improve the convergence rate of IWO while obtaining optimal solution. Additionally, we alleviate the limitation of QA (which is nothing but difficulty in escaping from a local optimum) by performing QA a predetermined number of times and then considering the average of all such solutions due to each iteration rather than a single solution. This technique makes our algorithm more efficient compared to the existing algorithms in the area. Twenty two benchmark problems and five real-life problems are adopted from literature to validate our proposed hybrid method QAIWO. The results of QAIWO are compared with the results obtained by the standard IWO and the well-known nature-inspired genetic algorithm (GA). These comparisons exhibit that QAIWO is more convenient to solve complex problems than using IWO and/or GA. Springer-Verlag Berlin Heidelberg, 2015 Invasive weed optimization nationallicence Quadratic approximation nationallicence Meta-heuristic optimization technique nationallicence Performance index nationallicence Naidu Y. Indian Institute of Technology, Bhubaneswar, India aut Ojha A. Indian Institute of Technology, Bhubaneswar, India aut Soft Computing Springer Berlin Heidelberg 19/12(2015-12-01), 3581-3598 1432-7643 19:12<3581 2015 19 500 https://doi.org/10.1007/s00500-015-1896-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-015-1896-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Naidu Y. Indian Institute of Technology, Bhubaneswar, India aut NATIONALLICENCE 700 1- Ojha A. Indian Institute of Technology, Bhubaneswar, India aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/12(2015-12-01), 3581-3598 1432-7643 19:12<3581 2015 19 500