Multi-Objective Performance Measurement: Alternatives To Par10 And Expected Running Time

LEARNING AND INTELLIGENT OPTIMIZATION, LION 12(2019)

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摘要
A multiobjective perspective onto common performance measures such as the PAR10 score or the expected runtime of single-objective stochastic solvers is presented by directly investigating the tradeoff between the fraction of failed runs and the average runtime. Multi-objective indicators operating in the bi-objective space allow for an overall performance comparison on a set of instances paving the way for instance-based automated algorithm selection techniques.
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关键词
Algorithm selection, Performance measurement
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