Hypervolume in biobjective optimization cannot converge faster than Ω(1/ p )
Author:
Affiliation:
1. Ecole Polytechnique, Palaiseau, France
2. Institut Polytechnique de Paris, Palaiseau, France
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3449639.3459371
Reference16 articles.
1. Theory of the hypervolume indicator
2. Theory of Evolution Strategies: A New Perspective. In Theory of Randomized Search Heuristics: Foundations and Recent Developments, A. Auger and B. Doerr (Eds.). World Scientific Publishing, Singapore;Auger A.;Chapter,2011
3. Convergence Rates of (1+1) Evolutionary Multiobjective Optimization Algorithms
4. The maximum hypervolume set yields near-optimal approximation
5. MultiGLODS: global and local multiobjective optimization using direct search
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1. Properties of Several Performance Indicators for Global Multi-Objective Simulation Optimization;2023 Winter Simulation Conference (WSC);2023-12-10
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