Abstract
One of important parts of every computer-aided multiple criteria decision support system is selection of a proper MCDM (Multiple Criteria Decision Making) method. WSM (Weighted Sum Model) and WPM (Weighted Product Model) are analyzed in the current research. The aim of the research is to measure the accuracy of the latter methods and to propose a method to increase the ranking accuracy of alternatives. It is proposed to apply joint WASPAS (Weighted Aggregates Sum Product Assessment) method. Methodology for evaluation of accuracy, based on initial criteria values, is developed. Optimization of weighted aggregated function is suggested, that enables to reach the highest accuracy of measurement. An example of application of the proposed methodology is presented. Ill. 3, bibl. 15, tabl. 4 (in English; abstracts in English and Lithuanian). DOI: http://dx.doi.org/10.5755/j01.eee.122.6.1810
Highlights
To design a high quality processes and to achieve effective decisions various computer-aided systems can be used
Effectiveness of computer-aided multiple criteria decision support system as well as accuracy of decisions is based on an application of a proper MCDM method
It was observed that Weighted Sum Model (WSM) and Weighted Product Model (WPM) methods can produce different ranking results
Summary
To design a high quality processes and to achieve effective decisions various computer-aided systems can be used. The very important step is to select the most suitable MCDM (Multiple Criteria Decision Making) method to determine the optimal alternative. Selection of MCDM methods based on various parameters was analyzed in a number of papers [1, 5,6,7, 10, 11]. Robustness of methods or their combination is analyzed [3, 13]. The authors of the current research propose to select an appropriate multiple criteria method based on its accuracy of estimation. Combination of two methods is proposed to increase the ranking accuracy. Optimization of aggregation is held and Weighted Aggregated Sum Product Assessment (WASPAS) method for ranking of alternatives is proposed. The method could be successfully applied in computeraided systems to support multiple criteria decisions
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