Download or read book Preference Aggregation and Conflict Modeling in Multi-attribute Decision Making written by and published by . This book was released on 2006 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supporting the decision of a group in engineering design is a challenging and complicated problem when issues like consensus and compromise must be taken into account. The Hypothetical Equivalents and Inequivalents Method (HEIM) has been developed to support decision making in multiattribute problems where one decision maker is making the decision. In this work HEIM is modified to support group decision making in multiattribute problems, resulting in the Group Hypothetical Equivalents and Inequivalents Method (Group-HEIM). Instead of aggregating attribute weights or overall alternative values from each individual as is common in other group decision methods, Group-HEIM operates by aggregating individual preferences. It is recognized that in group decision making, common preferences among group members can rarely be guaranteed, unless individual freedom is greatly limited. Group-HEIM instead allows individuals to freely express preferences over a number of hypothetical alternatives and then explores the level of conflict or differences from the aggregated group preferences. The relationship between the level of conflicting preferences and the usability of the resulting decision is also directly studied using the Group-HEIM. In addition, two fundamental extensions making Group-HEIM applicable to new classes of group decision problems. The first extension focuses on updating the formulation to place unequal importance on the preferences of the group members. The formulation presented in this dissertation allows team leaders to emphasize the input from certain group members based on experience or other factors. The second extension focuses on the theoretical implications of using a general class of aggregation functions. Illustration and validation of the developments are presented using a vehicle selection problem. Data from ten engineering design groups is used to demonstrate the application of the method.