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21 papers · 1 filter
An Evolutionary Algorithm Assisted by an Ensemble of Pareto-Optimal Surrogate Models
Kei Nishihara, Yaochu Jin, Masaya Nakata
An ensemble of surrogate models helps improve the prediction quality and robustness of surrogate models, and in turn, the search performance of surrogate-assisted evolutionary algo…
Weight Adaptation for Improving Parallel Performance of Adaptive Stochastic Natural Gradient
Yutaro Yamada, Kento Uchida, Shinichi Shirakawa
Probabilistic model-based evolutionary algorithms are promising for black-box optimization. Specifically, the adaptive stochastic natural gradient (ASNG) adaptively updates its lea…
Convergence Analysis of Evolution Strategies for Mixed-Integer Optimization
Ryoki Hamano, Kento Uchida, Shinichi Shirakawa
Mixed-integer extensions of evolution strategies (ES) that discretize selected coordinates of sampled continuous vectors often impose a lower bound on the standard deviation of int…
Benchmarking Stopping Criteria for Evolutionary Multi-objective Optimization
Kenji Kitamura, Ryoji Tanabe
Stopping criteria automatically determine when to stop an evolutionary algorithm, so as not to waste function evaluations on a stagnant population. Although stopping criteria play…
Analyzing the Landscape of the Indicator-based Subset Selection Problem
Keisuke Korogi, Ryoji Tanabe
The indicator-based subset selection problem (ISSP) involves finding a point subset that minimizes or maximizes a quality indicator. The ISSP is frequently found in evolutionary mu…
Speeding up Local Search for the Indicator-based Subset Selection Problem by a Candidate List Strategy
Keisuke Korogi, Ryoji Tanabe
In evolutionary multi-objective optimization, the indicator-based subset selection problem involves finding a subset of points that maximizes a given quality indicator. Local searc…