HPC Ranking of Big Performance Tableaux

Raymond Bisdorff

Chapter Chapter 11 in Algorithmic Decision Making with Python Resources, 2022, pp 137-147 from Springer

Abstract: Abstract The sparse outranking digraph, introduced in Chap. 9 , is suitable for tackling the ranking of big multiple-criteria performance tableaux with thousands or millions of records. To effectively compute rankings from performance tableaux of these sizes, we propose in this chapter a collection of C-compiled and optimised Digraph3 modules that may be run on HPC equipment as available, for instance, at the University of Luxembourg.

Date: 2022
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DOI: 10.1007/978-3-030-90928-4_11

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