投票和MCDM:萨里三角的教学法

Q4 Engineering
J. Hakula
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引用次数: 0

摘要

摘要本文有两个目标:首先,提出一个应用投票理论作为一种可能的评估方法,同时,提供一个教学框架,基于这一应用。评价和某些偏好和价值概念具有共同的语义根源。通过将偏好和选择等同起来,我们最终得到了社会选择(SC)理论和投票方法,它们也可以作为多标准决策(MCDM)中的联合决策来管理。在Saari三角的帮助下,可以描述至多三个选项的成对和位置投票规则的一些本质差异。投票或决策规则不一定遵循参与者的真实偏好,但可能反映所选规则的问题。通过投票和MCDM的虚构案例描述,萨里三角使得在数字网站的典型评估中可视化一些矛盾的结果成为可能。随着SC的候选人和选民被要求代表MCDM的替代方案和标准,本研究的方法和教学目标得以实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Voting and MCDM: the pedagogy of the Saari triangle
Abstract The essay has a twofold objective: primarily, to present an application of voting theory as a possible evaluation method, and concurrently, to offer a pedagogic framework, based on that very application. Evaluation and certain notions of preference and value have common semantic roots. By equating preference and choice, we end up amidst social choice (SC) theory and voting methods, also manageable as joint decisions in multiple-criteria decision making (MCDM). With the aid of the Saari triangle some essential differences of pairwise and positional voting rules for up to three alternatives can be depicted. A voting or decision rule does not necessarily follow the true preferences of the actors, but may mirror the problematics of the chosen rule. The Saari triangle makes it possible to visualize some paradoxical results in the exemplary evaluations of digital websites through an imaginary case description via voting and MCDM. As candidates and voters in SC are put to stand for alternatives and criteria in MCDM, the methodological and pedagogical goals of the study are achieved.
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来源期刊
Control and Cybernetics
Control and Cybernetics 工程技术-计算机:控制论
CiteScore
0.50
自引率
0.00%
发文量
0
期刊介绍: The field of interest covers general concepts, theories, methods and techniques associated with analysis, modelling, control and management in various systems (e.g. technological, economic, ecological, social). The journal is particularly interested in results in the following areas of research: Systems and control theory: general systems theory, optimal cotrol, optimization theory, data analysis, learning, artificial intelligence, modelling & identification, game theory, multicriteria optimisation, decision and negotiation methods, soft approaches: stochastic and fuzzy methods, computer science,
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