In the context of environmental, social, political, and
other circumstances, people make three sorts of judgements to indicate
importance, preference, or likelihood and use them to pick the best among
choices. They make these decisions based on recalled information or analysis of
advantages, costs, and dangers. We can occasionally construct standards of
excellence and poorness based on prior information and use them to rank the
choices one by one. This is important in instances when established norms must
be followed, such as student admissions and wage increases. Without standards,
one compares rather than rates options. Comparisons must be consistent within a
reasonable range. The rating and comparison procedures are both included in the
analytic hierarchy process (AHP). To decide the optimum choice, rationality
necessitates the creation of a trustworthy hierarchic structure or feedback
network that contains criteria of many forms of impact, stakeholders, and
decision alternatives [8].
The AHP technique was applied by Saaty and other writers in a wide range of
human activity areas, including planning, business, education, health-care, and
so on, but especially in management. In this work, we present two additional
proofs for the well-known assertion that for the eigenvector problem Aw = w,
the maximal eigenvalue, max, equals n. the solution vector w that represents
the probability components of discontinuous occurrences, and the consistent
matrix of pairwise comparisons of type n × n (n ≥ 2) We also provide an
approach for determining the eigenvalue issue solution Aw = nw, as well as a
flowchart to go with it. It is simple to design and apply the algorithm for
arbitrary consistent matrix A.
Author(s)
Details:
Miron Pavlus,
Faculty of Management, University of Prešov,
Konštantínova 16, 080 01 Prešov, Slovakia.
Rostislav Tomeš,
University College of Business in Prague, Spálená 14, 110 00 Prague, Czech
Republic.
Please see the link here: https://stm.bookpi.org/NRAMCS-V4/article/view/7042
