Titlebook: Evolutionary Multi-Criterion Optimization; 12th International C Michael Emmerich,André Deutz,Iryna Yevseyeva Conference proceedings 2023 Th

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Scalability of Multi-objective Evolutionary Algorithms for Solving Real-World Complex Optimization Positories), a machine-learning algorithm proposed by the authors. A theoretical comparison with a similar machine learning approach is made, pointing out some advantages of using the proposed algorithm using a benchmark problem designated by DTLZ5.Also, a real problem is used to show the effectiveness of the methodology.

agonist

A Relation Surrogate Model for Expensive Multiobjective Continuous and Combinatorial Optimizationbedded into a basic multiobjective evolutionary algorithm and applied to a set of continuous and combinatorial problems. The experimental results suggest that the relation model with the same settings can solve continuous and combinatorial problems, and it has an advantage in terms of problem scalability.

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0302-9743 held in Leiden, The Netherlands, during March 20-24, 2023...The 44 regular papers presented in this book were carefully reviewed and selected from 65 submissions...The papers are divided into the following topical sections: Algorithm Design and Engineering; Machine Learning and Multi-criterion Optim

BILIO

Conference proceedings 2023s...The papers are divided into the following topical sections: Algorithm Design and Engineering; Machine Learning and Multi-criterion Optimization; Benchmarking and Performance Assessment; Indicator Design and Complexity Analysis; Applications in Real World Domains; and Multi-Criteria Decision Making and Interactive Algorithms...

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0302-9743 ization; Benchmarking and Performance Assessment; Indicator Design and Complexity Analysis; Applications in Real World Domains; and Multi-Criteria Decision Making and Interactive Algorithms...978-3-031-27249-3978-3-031-27250-9Series ISSN 0302-9743 Series E-ISSN 1611-3349

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