Experiments in multiple criteria selection problems with multiple decision makers

Multiple Criteria Selection Problems (MCSP) deal with ranking alternatives under conflicting criteria. In the resolution of such problems scaling methods are used to standardize the data and weighting methods are used to assign a preference to each criterion based on the decision maker's assessment. Several methods have been proposed for weighting and scaling but the most favorable combinations of methods are uncertain. This study presents the results of experiments in which data from human decision makers is used to determine the best combination of weighting-scaling methods for single and multiple decision makers using the weighted sum decision making model.