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Near-Tight Runtime Guarantees for Many-Objective Evolutionary Algorithms

Main:53 Pages
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Abstract

Despite significant progress in the field of mathematical runtime analysis of multi-objective evolutionary algorithms (MOEAs), the performance of MOEAs on discrete many-objective problems is little understood. In particular, the few existing performance guarantees for classic MOEAs on classic benchmarks are all roughly quadratic in the size of the Pareto front.

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