A Bayesian Approach to Constrained Multi-objective Optimization

Paul Feliot; Julien Bect; Emmanuel Vázquez

doi:10.1007/978-3-319-19084-6_24

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A Bayesian Approach to Constrained Multi-objective Optimization

Paul Feliot Julien Bect Emmanuel Vázquez

Year: 2015 Lecture notes in computer science Pages: 256-261 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-319-19084-6_24

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Keywords:

Computer science Mathematical optimization Bayesian optimization Optimization problem Constraint (computer-aided design) Generalization Bayesian probability Constrained optimization Continuous optimization Nonlinear programming Test functions for optimization Derivative-free optimization Nonlinear system Algorithm Artificial intelligence Multi-swarm optimization Mathematics

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Advanced Multi-Objective Optimization Algorithms

Physical Sciences → Computer Science → Computational Theory and Mathematics

Optimal Experimental Design Methods

Social Sciences → Decision Sciences → Management Science and Operations Research

Water resources management and optimization

Physical Sciences → Engineering → Ocean Engineering

A Bayesian Approach to Constrained Multi-objective Optimization

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