Menu
Home
People
Places
Arts
History
Plants & Animals
Science
Life & Culture
Technology
Reference.org
Aggregated indices randomization method
open-in-new
<p>In applied mathematics and decision making, the aggregated indices randomization method (AIRM) is a modification of a well-known aggregated indices method, targeting complex objects subjected to multi-criteria estimation under uncertainty. AIRM was first developed by the Russian naval applied mathematician <a href="/facts/Aleksey_Krylov/3bycuHw2">Aleksey Krylov</a> around 1908. </p><p>The main advantage of AIRM over other variants of aggregated indices methods is its ability to cope with poor-quality input information. It can use non-numeric (<a href="/facts/Ordinal_number/GelFLjJt">ordinal</a>), non-exact (<a href="/facts/Interval_(mathematics)/e9se3vTe">interval</a>) and non-complete expert information to solve <a href="/facts/Multi-criteria_decision_analysis/IXQLJgBx">multi-criteria decision analysis</a> (MCDM) problems. An exact and transparent mathematical foundation can assure the precision and <a href="/facts/Fidelity/v0aRSvLu">fidelity</a> of AIRM results. </p>