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Computing Pareto‐optimal Predictor Composites for Complex Selection Decisions
Author(s) -
Druart Celina,
De Corte Wilfried
Publication year - 2012
Publication title -
international journal of selection and assessment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.812
H-Index - 61
eISSN - 1468-2389
pISSN - 0965-075X
DOI - 10.1111/ijsa.12001
Subject(s) - selection (genetic algorithm) , quality (philosophy) , pareto principle , pareto optimal , computer science , operations research , multi objective optimization , management science , operations management , machine learning , mathematics , economics , philosophy , epistemology
A complex selection situation encompasses vacancies for several different positions and applicants that apply simultaneously for one or several of these positions. This article presents an analytic method for estimating the expected selection quality, as well as the adverse impact ratio of these complex selections, when the decisions are based on a single predictor composite score. In addition, the method is integrated within a broader decision‐making framework for designing complex selection decisions that show a Pareto‐optimal balance between the selection quality and diversity goals. Finally, the decision aid is used to demonstrate the importance of applying the appropriate selection format (either the simple or the complex format) when exploring the front of Pareto‐optimal outcomes of planned selections.