Construction of a multiplicative-additive criteria convolution in the space of quantitative and qualitative indices to determine the priority of projects

V. Mamchuk
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Abstract

One of the main problems in scientific activity organization on a competitive basis is to improve methods of R&D project evaluation and priority determination. The project priority level may be determined using approaches based on the multi-attribute utility theory (MAUT), whose development is the subject matter of many studies and publications. Despite of the large number of publications on the subject, the development of a scientifically substantiated mathematical apparatus for multicriteria project evaluation is still a topical and challenging problem. The complexity of the development of project priority determination methods is due to difficulties in the construction of a unified rating scale that would allow one to measure the value of project indices differing in physical content and dimension. That is, what is difficult is the structurization of a decision-making person (DMP)’s preferences and the formalization of preference evaluation. It is also difficult to construct a criterion-target model that would adequately represent the system of DMP preferences in the form of a scalar value function, which is termed a criteria convolution, an integral criterion, or an integral value function (IVF). MAUT-based computational algorithms widely use procedures of common criteria scaling, in which one quality index is replaced with another. Such algorithms have a resolution equal to one; however, they operate with quantitative criteria alone, thus significantly narrowing their application area. Another drawback of theirs is the lack of simple methods to determine the value function at indifference (DMP preference equality) points. The aim of this work is to eliminate these drawbacks in a multiplicative-additive IVF model. To do this, the following was done. Functional relationships between DMP preferences and alternative quality indices were established to give analytical expressions for evaluating local value functions at indifference points. A method was developed for constructing a multiplicative-additive criteria convolution to evaluate and rank alternatives in the space of quantitative and qualitative indices. An algorithm was developed to determine the priority of projects; the algorithm allows one to rank alternatives with a resolution equal to one. In this work, decision theory, multicriteria utility theory, and verbal decision analysis methods were used. The results obtained may be used in R&D efficiency evaluation, competitive project selection, and space program formation in the rocket space industry.
构造一个乘加准则卷积空间的定量和定性指标来确定项目的优先级
在竞争基础上组织科技活动的主要问题之一是改进科研项目评价和优先级确定的方法。项目优先级可以使用基于多属性效用理论(MAUT)的方法来确定,该理论的发展是许多研究和出版物的主题。尽管在这个问题上有大量的出版物,但为多标准项目评估开发一个有科学依据的数学仪器仍然是一个热门和具有挑战性的问题。项目优先级确定方法的复杂性是由于难以建立统一的评级量表来衡量不同物理内容和维度的项目指标的价值。也就是说,难点在于决策者偏好的结构化和偏好评价的形式化。也很难构建一个标准-目标模型,以标量值函数的形式充分表示DMP偏好系统,这被称为标准卷积、积分标准或积分值函数(IVF)。基于maut的计算算法广泛使用通用准则缩放程序,其中一个质量指标被另一个质量指标取代。这种算法的分辨率等于1;然而,它们单独使用定量标准,因此大大缩小了它们的应用范围。他们的另一个缺点是缺乏确定无差异(DMP偏好相等)点的价值函数的简单方法。这项工作的目的是消除这些缺点,在一个乘法-加法体外受精模型。为此,我们做了以下工作。建立了DMP偏好与备选质量指标之间的函数关系,给出了无差异点局部价值函数的解析表达式。提出了一种构造乘加性准则卷积的方法,对定量和定性指标空间中的备选方案进行评价和排序。开发了一种算法来确定项目的优先级;该算法允许人们以等于1的分辨率对备选方案进行排序。在这项工作中,决策理论,多标准效用理论和口头决策分析方法被使用。所得结果可用于火箭航天工业的研发效率评价、竞争性项目选择和空间计划制定。
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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