The Gradient Subspace Approximation and Its Application to Bi-objective Optimization Problems

DOI10.1007/978-3-030-51264-4_15zbMath1454.65041OpenAlexW3045144058MaRDI QIDQ5131688

Adriana Lara, Oliver Schütze, Lourdes Uribe

Publication date: 9 November 2020

Published in: Advances in Dynamics, Optimization and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-51264-4_15

zbMATH Keywords

bi-objective optimizationdescent directionsgradient free optimizationgradient subspace approximation

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Multi-objective and goal programming (90C29) Approximation methods and heuristics in mathematical programming (90C59)

Uses Software

• SMS-EMOA

Cites Work

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• Stochastic method for the solution of unconstrained vector optimization problems
• Multiobjective search algorithm with subdivision technique
• SMS-EMOA: multiobjective selection based on dominated hypervolume
• Steepest descent methods for multicriteria optimization.
• Nonlinear multiobjective optimization. A generalized homotopy approach
• Gradient subspace approximation: a direct search method for memetic computing
• Covering Pareto sets by multilevel subdivision techniques
• Trade-off analysis approach for interactive nonlinear multiobjective optimization
• On the hierarchical structure of Pareto critical sets
• Cell Mapping Methods
• Evaluating Derivatives
• Newton's Method for Multiobjective Optimization
• Evolutionary Algorithms for Solving Multi-Objective Problems
• The directed search method for multi-objective memetic algorithms

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