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Updating Weight Vectors Using Subset Selection from an Unbounded External Archive for Evolutionary Multi-Objective Optimization
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Two-Stage Greedy Approximated Hypervolume Subset Selection for Large-Scale Problems
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Generic Postprocessing via Subset Selection for Hypervolume and Epsilon-Indicator
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Clustering-Based Selection for Evolutionary Many-Objective Optimization
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Modified Distance Calculation in Generational Distance and Inverted Generational Distance
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A Study of the Parallelization of a Coevolutionary Multi-objective Evolutionary Algorithm
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Multiobjective optimization for crash safety design of vehicles using stepwise regression model
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A benchmark test suite for evolutionary many-objective optimization
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A repository of real-world datasets for data-driven evolutionary multiobjective optimization
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An easy-to-use real-world multi-objective optimization problem suite
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Implicit enumeration strategies for the hypervolume subset selection problem
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Engineering applications of multi-objective evolutionary algorithms: A test suite of box-constrained real-world problems
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Multiobjective evolutionary algorithms: A survey of the state of the art
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On the use of two reference points in decomposition based multiobjective evolutionary algorithms
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A modified PBI approach for multi-objective optimization with complex Pareto fronts
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Evolutionary algorithm using adaptive fuzzy dominance and reference point for many-objective optimization
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Adaptive Epsilon dominance in decomposition-based multiobjective evolutionary algorithm
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Modeling and optimization of the combined carbon dioxide reforming and partial oxidation of natural gas
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Scalable multi-objective optimization test problems
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Maximising Hypervolume for Selection in Multi-objective Evolutionary Algorithms
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A clustering based multiobjective evolutionary algorithm
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A two-phase many-objective evolutionary algorithm with penalty based adjustment for reference lines
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A multi-objective evolutionary algorithm based on an enhanced inverted generational distance metric
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Decomposition Based Evolutionary Algorithm with a Dual Set of reference vectors
inferredcites →https://doi.org/10.1109/cec.2019.8790342openalex-snapshot
Regular Pareto Front Shape is not Realistic
inferredcites →https://doi.org/10.1109/cec48606.2020.9185734openalex-snapshot
Modified Distance-based Subset Selection for Evolutionary Multi-objective Optimization Algorithms
inferredcites →https://doi.org/10.1109/cec48606.2020.9185878openalex-snapshot
Lazy Greedy Hypervolume Subset Selection from Large Candidate Solution Sets
inferredcites →https://doi.org/10.1109/fuzzy.2009.5277324openalex-snapshot
Selecting a small number of representative non-dominated solutions by a hypervolume-based solution selection approach
inferredcites →https://doi.org/10.1109/jas.2021.1003817openalex-snapshot
A Survey of Evolutionary Algorithms for Multi-Objective Optimization Problems With Irregular Pareto Fronts
inferredcites →https://doi.org/10.1109/mci.2017.2742868openalex-snapshot
PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum]
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Clustering-Based Subset Selection in Evolutionary Multiobjective Optimization
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An Improved Multiobjective Optimization Evolutionary Algorithm Based on Decomposition for Complex Pareto Fronts
inferredcites →https://doi.org/10.1109/tcyb.2016.2586191openalex-snapshot
Decomposition-Based-Sorting and Angle-Based-Selection for Evolutionary Multiobjective and Many-Objective Optimization
inferredcites →https://doi.org/10.1109/tcyb.2017.2737519openalex-snapshot
An Enhanced Decomposition-Based Evolutionary Algorithm With Adaptive Reference Vectors
inferredcites →https://doi.org/10.1109/tcyb.2017.2737554openalex-snapshot
A Decomposition-Based Many-Objective Evolutionary Algorithm With Two Types of Adjustments for Direction Vectors
inferredcites →https://doi.org/10.1109/tcyb.2018.2834466openalex-snapshot
A Clustering-Based Adaptive Evolutionary Algorithm for Multiobjective Optimization With Irregular Pareto Fronts
inferredcites →https://doi.org/10.1109/tcyb.2018.2872803openalex-snapshot
Evolutionary Many-Objective Optimization Based on Adversarial Decomposition
inferredcites →https://doi.org/10.1109/tcyb.2020.3020630openalex-snapshot
An Adaptive Reference Vector-Guided Evolutionary Algorithm Using Growing Neural Gas for Many-Objective Optimization of Irregular Problems
inferredcites →https://doi.org/10.1109/tevc.2005.861417openalex-snapshot
A review of multiobjective test problems and a scalable test problem toolkit
inferredcites →https://doi.org/10.1109/tevc.2007.892759openalex-snapshot
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
inferredcites →https://doi.org/10.1109/tevc.2013.2281534openalex-snapshot
An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point Based Nondominated Sorting Approach, Part II: Handling Constraints and Extending to an Adaptive Approach
inferredcites →https://doi.org/10.1109/tevc.2013.2281535openalex-snapshot
An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints
inferredcites →https://doi.org/10.1109/tevc.2014.2373386openalex-snapshot
An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition
inferredcites →https://doi.org/10.1109/tevc.2015.2504730openalex-snapshot
Pareto or Non-Pareto: Bi-Criterion Evolution in Multiobjective Optimization
inferredcites →https://doi.org/10.1109/tevc.2016.2519378openalex-snapshot
A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization
inferredcites →https://doi.org/10.1109/tevc.2016.2587749openalex-snapshot
Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes
inferredcites →https://doi.org/10.1109/tevc.2017.2695579openalex-snapshot
Self-Organizing Map-Based Weight Design for Decomposition-Based Many-Objective Evolutionary Algorithm
inferredcites →https://doi.org/10.1109/tevc.2017.2704118openalex-snapshot
On Tchebycheff Decomposition Approaches for Multiobjective Evolutionary Optimization
inferredcites →https://doi.org/10.1109/tevc.2017.2729550openalex-snapshot
Computing and Updating Hypervolume Contributions in Up to Four Dimensions
inferredcites →https://doi.org/10.1109/tevc.2017.2749619openalex-snapshot
An Indicator-Based Multiobjective Evolutionary Algorithm With Reference Point Adaptation for Better Versatility
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Learning to Decompose: A Paradigm for Decomposition-Based Multiobjective Optimization
inferredcites →https://doi.org/10.1109/tevc.2018.2883094openalex-snapshot
Distance-Based Subset Selection for Benchmarking in Evolutionary Multi/Many-Objective Optimization
inferredcites →https://doi.org/10.1109/tevc.2019.2926151openalex-snapshot
Adapting Reference Vectors and Scalarizing Functions by Growing Neural Gas to Handle Irregular Pareto Fronts
inferredcites →https://doi.org/10.1109/tevc.2020.2978158openalex-snapshot
A Survey of Weight Vector Adjustment Methods for Decomposition-Based Multiobjective Evolutionary Algorithms
inferredcites →https://doi.org/10.1109/tevc.2023.3261134openalex-snapshot
Subset Selection for Evolutionary Multiobjective Optimization
inferredcites →https://doi.org/10.1109/tsmc.2022.3187370openalex-snapshot
Coordinated Adaptation of Reference Vectors and Scalarizing Functions in Evolutionary Many-Objective Optimization
inferredcites →https://doi.org/10.1137/s1052623496307510openalex-snapshot
Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems
inferredcites →https://doi.org/10.1145/3071178.3071339openalex-snapshot
Adaptive weights generation for decomposition-based multi-objective optimization using Gaussian process regression
inferredcites →https://doi.org/10.1145/3205455.3205648openalex-snapshot
MOEA/D with uniformly randomly adaptive weights
inferredcites →https://doi.org/10.1145/3449639.3459391openalex-snapshot
Distance-based subset selection revisited
inferredcites →https://doi.org/10.1155/2020/8796738openalex-snapshot
Multiobjective Optimization of Milling Parameters for Ultrahigh‐Strength Steel AF1410 Based on the NSGA‐II Method
inferredcites →https://doi.org/10.1162/evco_a_00109openalex-snapshot
MOEA/D with Adaptive Weight Adjustment
inferredcites →https://doi.org/10.1162/evco_a_00157openalex-snapshot
Hypervolume Subset Selection in Two Dimensions: Formulations and Algorithms
inferredcites →https://doi.org/10.1162/evco_a_00226openalex-snapshot
How to Specify a Reference Point in Hypervolume Calculation for Fair Performance Comparison
inferredcites →https://doi.org/10.1162/evco_a_00269openalex-snapshot
What Weights Work for You? Adapting Weights for Any Pareto Front Shape in Decomposition-Based Evolutionary Multiobjective Optimisation
inferredcites →https://doi.org/10.48550/arxiv.2006.08156openalex-snapshot
Solution Subset Selection for Final Decision Making in Evolutionary Multi-Objective Optimization
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Clustering-Based Subset Selection in Evolutionary Multiobjective Optimization
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