Improving case-based reasoning with the aid of multi-criteria and group decision-making methods

摘要

Solving semi-formalized and semi-structured tasks on the basis of a case-based reasoning (CBR) provides to use the accumulated knowledge and experience. Wherein, sometimes it is necessary to improve CBR results, for example, to reduce the set of possible solutions and to ground their correctness not only with the use of a similarity measure. One way to solve this problem is to use mathematical multi-criteria and group decision-making methods. This paper discusses the combined use of the ARAMIS (Aggregation and Ranking Alternatives nearby the Multi-Attribute Ideal Situation), AIR (Aggregation of Individual Ranking), MOPC (Method Of Pairwise Comparison processing), COIP (Complex processing Of Individual Preferences) and a case-based reasoning. The algorithm and case study for solving problem of selecting construction materials in petrochemistry are described. The application of the approach did not result to new decisions and/or the revision of decisions based on a case-based reasoning approach. But it provides their grounding from the point of view of mathematical methods and the growth of confidence from the point of view of the experts.