集成线性物理规划和模糊逻辑的机器人选择

M. A. Ilgin
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引用次数: 3

摘要

越来越多的公司正在使用机器人来执行各种重复性和危险的任务。许多不同的机器人替代品的存在迫使公司在确定最合适的机器人替代品之前考虑几个相互冲突的标准。为了帮助决策者在机器人选择过程中进行决策,研究人员开发了各种基于多准则的决策方法。然而,这些方法要求决策者给评价标准赋予物理上毫无意义的权重。本文通过提出一种基于线性物理规划的机器人选择方法,消除了这种权重分配过程。此外,为了确定机器人主观评价标准的偏好值,本文还将模糊逻辑融入到该方法中。为了说明所提出方法的适用性,文中还给出了一个数值算例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrating Linear Physical Programming and Fuzzy Logic for Robot Selection
An increasing number of companies are using robots to perform a variety of repetitive and hazourdous tasks. Existence of many different robot alternatives force companies to consider several conflicting criteria before determining the most suitable robot alternative. Researchers have developed various multi-criteria decision making based methodologies in order to assist the decision makers in robot selection process. However, those methodologies require decision makers to assign physically meaningless weights to evaluation criteria. This article eliminates this weight assignment process by proposing a robot selection methodology based on linear physical programming. In addition, fuzzy logic was integrated into the proposed approach in order to determine the preference values of subjective robot evaluation criteria. A numerical example is also provided in order to present the applicability of the proposed methodology.
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