研究多属性模型中遗漏目标成本影响因素的模拟方法

IF 1.9 Q3 MANAGEMENT
Sarah A. Kusumastuti, Richard S. John
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引用次数: 0

摘要

经验证据表明,决策者没有能力确定决策问题中的所有相关目标。我们采用蒙特卡罗模拟法,将基准模型与仅包含目标子集的简化模型进行比较,研究了不完整目标集的影响。我们评估了目标数量、备选方案数量、目标间相关性和属性权重不同的简化模型的性能。结果表明,目标缺失对目标间负相关的多属性模型影响最大;同样,目标权重相同的模型比权重不等的模型受到的影响更大。在目标缺失比例相同的情况下,目标较多的决策问题受目标缺失的影响往往较小。相反,备选方案较多的决策问题在某些性能指标上受到的影响较大,而在其他性能指标上受到的影响较小。不过,与目标之间的相关性相比,目标和备选方案数量对模型性能的影响相对较小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A simulation approach to investigate factors influencing the cost of omitted objectives in multiattribute models

Empirical evidence suggests that decision-makers are ill-equipped to identify all relevant objectives in a decision problem. We examine the effect of an incomplete set of objectives using a Monte Carlo simulation to compare a baseline model to a reduced model incorporating only a subset of objectives. We assess the performance of reduced models varying in the number of objectives, the number of alternatives, the correlations among objectives, and attribute weights. Results suggest that missing objectives will most impact multiattribute models with negative correlations between objectives; similarly, models with equally weighted objectives suffer more than models with unequal weights. Decision problems with more objectives tend to be less impacted by missing objectives, given the same proportion of missing objectives. In contrast, decision problems with more alternatives are more impacted for some performance measures but less on others. However, the variation in model performance due to the number of objectives and alternatives is relatively minor compared to the variation due to the nature of the correlation between objectives.

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来源期刊
CiteScore
4.70
自引率
10.00%
发文量
14
期刊介绍: The Journal of Multi-Criteria Decision Analysis was launched in 1992, and from the outset has aimed to be the repository of choice for papers covering all aspects of MCDA/MCDM. The journal provides an international forum for the presentation and discussion of all aspects of research, application and evaluation of multi-criteria decision analysis, and publishes material from a variety of disciplines and all schools of thought. Papers addressing mathematical, theoretical, and behavioural aspects are welcome, as are case studies, applications and evaluation of techniques and methodologies.
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