Weighting Methods for Multi-Criteria Decision Making Technique

Weighting Methods for Multi-Criteria Decision Making Technique
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DOI:
10.4314/jasem.v23i8.7
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发表时间:
2019-08-01
期刊:
Journal of Applied Sciences & Environmental Management
影响因子:
--
通讯作者:
Odu, G. O.
Odu, G. O.
中科院分区:
其他
文献类型:
--
作者:
Odu, G. O.

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确定标准权重是许多多标准决策(MCDM)技术中经常出现的问题。考虑到标准权重能够显着影响决策过程的结果,因此需要特别关注标准权重的客观性因素。本文概述了适用于多标准优化技术的不同加权方法。文献中报道了许多对于解决多标准问题非常有用的概念。目前的工作强调使用这些加权方法来确定每个标准的标准偏好,以带来理想的属性,并通过识别可能的最佳选项来建立和满足所有选定标准的多重性能衡量标准。结果表明,主观赋权方法在计算上比客观赋权方法简单、直接,客观赋权方法采用数学函数从每个标准中获取信息来确定权重,而无需决策者的输入。这可以从成对比较中看出,智能手机的内部存储器和随机存取存储器的权重值分别为0.33和0.22,因为它们具有最高的标准权重。版权所有 (C) 2019 奥都。
Determining criteria weights is a problem that arises frequently in many multi-criteria decision-making (MCDM) techniques. Taking into account the fact that the weights of criteria can significantly influence the outcome of the decision-making process, it is important to pay particular attention to the objectivity factors of criteria weights. This paper provides an overview of different weighting methods applicable to multi-criteria optimization techniques. There are a lot of concept been reported from the literature that are very useful in solving multicriteria problems. The present work emphasized on the use of these weighting methods in determining the criteria preference of each criterion to bring about desirable properties and in order to establish and satisfy a multiple measure of performance across all the criteria selected by identifying the best options possible. And from the results, it shows that subjective weighting methods are easy and straight forward in terms of their computations than the objective weighting methods which derived their information from each criterion by adopting a mathematical function to determine the weights without the decision-maker's input,. This can be seen from the pairwise comparison which gives an internal storage and random access memory of a smart phone a weight value of 0.33 and 0.22 respectively as they have the highest criteria weights. Copyright (C) 2019 Odu.