A new fuzzy multi-objective optimisation method with desirability function under uncertainty

Peyman Soleymani, S. Mousavi, B. Vahdani, A. Aboueimehrizi
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引用次数: 4

Abstract

Step method (STEM) is one of the most efficient and usable method of multi-objective decision making (MODM), and it is in the interactive category which uses decision makers (DMs) preference information during problem solving. In recent years, step method (STEM) has been developed based on the desirability function, namely D-STEM, in which the shortcoming of the STEM has been removed. To confront the problem in the real-world, paying attention to imprecision and uncertainty in decision making should be considered; however, in such status, D-STEM is unable to solve complex problem under uncertainty. In this paper, a new version of multi-objective optimisation method under a fuzzy environment with desirability function concept, namely FD-STEM, is proposed to deal with uncertain and imprecise conditions. Fuzzy uncertainties and imprecisions are considered in all parameters including objective coefficient, technologic coefficient, resources and decision variables as a fully fuzzy multi-objective optimisation. Finally, in an application example, decision making in manufacturing industry is presented and discussed based on consequents of fuzzy desirability function and with a fuzzy ranking function. Also, by using transformation method, the application example is solved and based on the overall desirability they are compared.
不确定条件下带理想函数的模糊多目标优化方法
步进法(STEM)是多目标决策(MODM)中最有效、最实用的方法之一,它是利用决策者在问题求解过程中的偏好信息进行决策的交互式方法。近年来,基于期望函数的步进法(STEM)得到了发展,即D-STEM,它消除了STEM的缺点。面对现实世界中的问题,要注意决策的不精确性和不确定性;然而,在这种状态下,D-STEM无法解决不确定性下的复杂问题。本文提出了一种具有理想函数概念的模糊环境下多目标优化方法FD-STEM,用于处理不确定和不精确的条件。将目标系数、技术系数、资源和决策变量等参数考虑为全模糊多目标优化。最后,通过一个应用实例,给出并讨论了基于模糊期望函数结果和模糊排序函数的制造业决策。并利用变换方法对应用实例进行了求解,并在总体满意度的基础上对两者进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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