Paper Title:
Method of Product Innovation Acquisition Based on Dynamic Response Particle Swarm Optimization
| Periodical | Advanced Materials Research (Volumes 542 - 543) |
|---|---|
| Main Theme | Automatic Manufacturing Systems II |
| Edited by | Runhua Tan, Jibing Sun and Qingsuo Liu |
| Pages | 3-7 |
| DOI | 10.4028/www.scientific.net/AMR.542-543.3 |
| Citation | Yan Chao Yin et al., 2012, Advanced Materials Research, 542-543, 3 |
| Online since | June, 2012 |
| Authors | Yan Chao Yin, Ya Yu Huang |
| Keywords | Dynamic Nonlinear Optimization, Dynamic Response Particle Swarm Optimization (DRPSO), Product Innovation Acquisition, Uncertain Front End |
| Price | US$ 28,- |
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Abstract
In order to accurately locate the changing demands and objects of customers, a novel mining algorithm was presented to predict the Optimum Customer Demand (OCD) in the uncertain front end, which can be formulated as a dynamic nonlinear optimization problem. The improved Particle Swarm Optimization involves accurately detecting the changes all of the search space and reliably updating obsolete particle memories, which has been shown to be effective in locating the changing plentiful innovative thinking. Finally, the algorithm is applied into the prediction of customer demands in car’s appearance feature, which effectively guide the implementation of product innovation and greatly improve the front end performance.
