Ann Oper Res https://doi.org/10.1007/s10479-018-2905-0 ORIGINAL RESEARCH 1 2 2 Fawaz Alsolami · Talha Amin · Igor Chikalov · Mikhail Moshkov © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract We consider bi-criteria optimization problems for decision rules and rule systems relative to length and coverage. We study decision tables with many-valued decisions in which each row is associated with a set of decisions as well as single-valued decisions where each row has a single decision. Short rules are more understandable; rules covering more rows are more general. Both of these problems—minimization of length and maximization of coverage of rules are NP-hard. We create dynamic programming algorithms which can ﬁnd the minimum length and the maximum coverage of rules, and can construct the set of Pareto optimal points for the corresponding bi-criteria optimization problem. This approach is applicable for medium-sized decision tables. However, the considered approach allows us to evaluate the quality of various heuristics for decision rule construction which are applicable for relatively big datasets. We can evaluate these heuristics from the point of view of (i) single-criterion—we can compare the length or coverage of rules constructed by heuristics; and (ii) bi-criteria—we can measure the distance of
Annals of Operations Research – Springer Journals
Published: Jun 5, 2018
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