03714nas|a2200397 i 4500 20260818114448.0 290296s1995 th uu m rtt 00| a1eng d .b11425349 AIT RSPR no. IE-95-1 Xiong, Dongwei A framework of more intelligent multicriteria decision support for selection and ranking Bangkok : Asian Institute of Technology, 1995 48 leaves Research studies project report ; no. IE-95-1 A research study submitted in partial fulfillment of the requirement for the degree of Master of Engineering, School of Engineering and Technology Research Studies Project Report (M. Sc.) - Asian Institute of Technology, 1995 In most of real word contexts, decisions must be made in presence of multiple, competing and conflicting criteria. Such decision making problems fall down multicriteria decision making (MCDM) domain. This study aims to formulate a framework to solve discrete multicriteria decision making problems by utilizing artificial intelligent decision support systems, and the method used in this study is to integrate Decision Support System (DSS) and Expert System (ES) technologies into MCDM. The major advantage of this approach is that all the data, such as aggregation properties, MCDM methods, rules, and the DM's preferences and feelings, can be integrated into a logical structure, which supports the decision maker (DM) in all aspects of model building, and allows the DM to directly involve in MCDM processes. The system consists of a user-friendly interface, a problem editor, a data translator, a knowledge-based MCDM method choice sub-system, a review analysis sub-system and a data base management system. The problem editor helps the DM to generate fully expended alternatives, design the weights of criteria, and transform the descriptive data of multiattribute problems, by rules, into a manageable decision matrix; the data translator aims to prepare the data which are to be used by any MCDM method; the method choice sub-system allows the DM to flexibly choose a suitable MCDM method among the model base and the sequence of MCDM methods to solve decision problems; and the review analysis sub-system enables the DM to make a comparative analysis of the results in order to gain new insights not only into the problem, but also into the working of the methods as well as their adequacy to the types of problems and DMs; the data base management system stores factual information and provides data to MCDM models and the DM during the problem solving process. Artificial intelligence Decision support systems Pastijn, Hugo, Chairperson Tabucanon, Mario T., Examination Committee Tang, John C.S., Examination Committee Asian Institute of Technology Partial, Scholarship Donor Asian Institute of Technology. Research studies project report ; no. IE-95-1 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B15467 .b11425349 mnait v 240404 0 960229 m a v 2 mnait mnarc 22 40 Barcode : 30050120724017 CREATED : 2012-10-19 RECORD # : i12707168 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 1 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050160109194 CREATED : 2016-08-04 RECORD # : i12933545 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 47235 47235 0 0 0 0 MAIN MAIN mnait 2026-08-18 0 AIT RSPR no. IE-95-1 30050120724017 2026-08-18 11:44:48 3 2026-08-18 22 0 0 0 0 MAIN MAIN mnarc 2026-08-18 0 AIT RSPR no. IE-95-1 30050160109194 2026-08-18 11:44:48 2026-08-18 40