Computing the Set of Approximate Solutions of a Multi-objective Optimization Problem by Means of Cell Mapping Techniques

DOI10.1007/978-3-319-01128-8_12zbMath1322.90083OpenAlexW165931059MaRDI QIDQ2950784

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Publication date: 9 October 2015

Published in: EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-01128-8_12

zbMATH Keywords

global optimizationmulti-objective optimizationapproximate solutionscell mapping techniques

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Multi-objective and goal programming (90C29)

Related Items (4)

Multi-Objective Optimization of Active Vehicle Suspension System Control ⋮ Parallel Cell Mapping for Unconstrained Multi-Objective Optimization Problems ⋮ A New Predictor Corrector Variant for Unconstrained Bi-objective Optimization Problems ⋮ A Memetic Variant of R-NSGA-II for Reference Point Problems

Uses Software

• NBI
• MOEA/D

Cites Work

• Unnamed Item
• A multi-objective approach to the design of low thrust space trajectories using optimal control
• Stochastic method for the solution of unconstrained vector optimization problems
• A discrete method of optimal control based upon the cell state space concept
• Multiobjective search algorithm with subdivision technique
• \(\epsilon\)-solutions in vector minimization problems
• Cell-to-cell mapping. A method of global analysis for nonlinear systems
• A subdivision algorithm for the computation of unstable manifolds and global attractors
• Steepest descent methods for multicriteria optimization.
• Stochastic optimal control via Bellman's principle.
• Lectures on analysis on metric spaces
• Nonlinear multiobjective optimization. A generalized homotopy approach
• Covering Pareto sets by multilevel subdivision techniques
• Unbiased approximation in multicriteria optimization
• Gap-free computation of Pareto-points by quadratic scalarizations
• Adaptive Scalarization Methods in Multiobjective Optimization
• Application of a cell-mapping method to optimal control problems
• A Theory of Cell-to-Cell Mapping Dynamical Systems
• Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems
• Evolutionary Algorithms for Solving Multi-Objective Problems
• The directed search method for multi-objective memetic algorithms

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