Revisiting norm optimization for multi-objective black-box problems: a finite-time analysis

DOI10.1007/s10898-018-0709-zzbMath1420.90063arXiv1804.11020OpenAlexW2798391809MaRDI QIDQ2416585

Yanyan Li

Publication date: 23 May 2019

Published in: Journal of Global Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1804.11020

zbMATH Keywords

multi-objective optimizationderivative-free optimizationblack-box optimizationfinite-time analysis

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Derivative-free methods and methods using generalized derivatives (90C56)

Uses Software

• SymPy
• MSO

Cites Work

• Unnamed Item
• MSO: a framework for bound-constrained black-box global optimization algorithms
• Multi-objective simultaneous optimistic optimization
• Nonlinear multiobjective optimization
• An algorithm of simplicial Lipschitz optimization with the bi-criteria selection of simplices for the bi-section
• A naive multi-scale search algorithm for global optimization problems
• Direct Multisearch for Multiobjective Optimization
• On compromise solutions in multiple objective programming
• From Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planning

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