Yang Yan-Pu
School of Construction Machinery, Chang'an University, Xi'an 710064, China.
Comput Intell Neurosci. 2017;2017:9740278. doi: 10.1155/2017/9740278. Epub 2017 Feb 12.
Consumers' opinions toward product design alternatives are often subjective and perceptual, which reflect their perception about a product and can be described using Kansei adjectives. Therefore, Kansei evaluation is often employed to determine consumers' preference. However, how to identify and improve the reliability of consumers' Kansei evaluation opinions toward design alternatives has an important role in adding additional insurance and reducing uncertainty to successful product design. To solve this problem, this study employs a consensus model to measure consistence among consumers' opinions, and an advanced particle swarm optimization (PSO) algorithm combined with Linearly Decreasing Inertia Weight (LDW) method is proposed for consensus reaching by minimizing adjustment of consumers' opinions. Furthermore, the process of the proposed method is presented and the details are illustrated using an example of electronic scooter design evaluation. The case study reveals that the proposed method is promising for reaching a consensus through searching optimal solutions by PSO and improving the reliability of consumers' evaluation opinions toward design alternatives according to Kansei indexes.
消费者对产品设计方案的看法往往是主观的和感性的，这些看法反映了他们对产品的认知，并且可以用感性形容词来描述。因此，感性评价常常被用来确定消费者的偏好。然而，如何识别并提高消费者对设计方案的感性评价意见的可靠性，对于为成功的产品设计增加额外保障并降低不确定性具有重要作用。为了解决这个问题，本研究采用一种共识模型来衡量消费者意见之间的一致性，并提出了一种结合线性递减惯性权重（LDW）方法的改进粒子群优化（PSO）算法，通过最小化消费者意见的调整来达成共识。此外，介绍了所提方法的流程，并以电动滑板车设计评价为例说明了细节。案例研究表明，所提方法有望通过粒子群优化搜索最优解来达成共识，并根据感性指标提高消费者对设计方案评价意见的可靠性。
