层次分析法
托普西斯
排名(信息检索)
多准则决策分析
计算机科学
挖掘机
过程(计算)
维柯法
运筹学
选择(遗传算法)
人工智能
数学
工程类
机械工程
操作系统
作者
Snezana Savkovic,Predrag Jovančić,Stevan Djenadic,Miloš Tanasijević,Filip Miletić
标识
DOI:10.1016/j.eswa.2022.117199
摘要
This paper presents a methodology for evaluating and ranking different bucket wheel excavators (BWE) for determining which machine should enter in the process of revitalization and modernization. Various multicriteria methods are used. Combining them achieves the best effect when choosing BVE for the modernization process. AHP, TOPSIS, VIKOR, and PROMETHEE methods are used. The hybrid models are developed from the multi-criteria decision making (MCDM) methods and they are used to evaluate the basic indicators that characterize the operation of a BWE. The methods will be applied to each group of the parameters, their sub-parameters and alternatives in the selection. The models are defined in two parts. In the first part, the priority vectors of parameters are defined by applying the AHP method. Other methods are applied in the second part where the evaluation of alternatives is made according to the defined parameters. That forms three partial hybrid models AHP-TOPSIS, AHP-VIKOR, AHP-PROMETHEE. The analysis parameters are qualified in four groups Technical, Working, Maintenance, and Economics parameters. Validation and selection of the optimal method will be performed in relation to the expert analysis with prepared questionnaires. The selected method should help in defining which machine will enter in the process of revitalization and modernization. According to this method, there is a 100% match with AHP-PROMETHEE, and the ranking given with AHP-TOPSIS corresponds to 75%, while AHP-VIKOR corresponds to 50%. Model AHP-PROMETHEE for the selecting of the BWE is a reliable and suitable tool for this purpose. In comparison to the classical statistical methods, this approach can achieve great saving. The BWE are very expensive machines and their value is 20–30 million euros. The investment in revitalization and modernization is 25–35% of the purchase price. This explains the importance of forming such an evaluation model. The presented analysis showed the possibility of the application of hybrid combined methods. The results in the paper presented the benefit from two aspects. The first aspect is the formation of a model that can be applied to other similar problems. Another aspect is the choice of the machine itself based on a complex analysis of a large number of parameters. Generally, the model becomes universal and can be used for later similar analyzes.
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