An Indicator-Based Multiobjective Evolutionary Algorithm With Reference Point Adaptation for Better Versatility
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- Type
- article
- Published
- 2018-08-01
- Cited by
- 601
- References
- 68
- Access
- Open access
- OpenAlex
- https://openalex.org/W2751605210
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:21948272
Keywords
Evolutionary algorithm, Multi-objective optimization, Mathematical optimization, Computer science, Pareto principle
References
- PESA-II: region-based selection in evolutionary multiobjective optimization
- GDE-MOEA: A new MOEA based on the generational distance indicator and ε-dominance
- A combined genetic adaptive search (GeneAS) for engineering design
- Multi-objective optimization using evolutionary algorithms
- An Efficient Approach to Nondominated Sorting for Evolutionary Multiobjective Optimization
- A Multiobjective Evolutionary Algorithm Using Gaussian Process-Based Inverse Modeling
- Preference-Inspired Coevolutionary Algorithms for Many-Objective Optimization
- Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multiobjective Optimization
- Finding evenly spaced fronts for multiobjective control via averaging Hausdorff-measure
- Objective Reduction in Many-Objective Optimization: Linear and Nonlinear Algorithms
- Multiobjective evolutionary algorithms: A survey of the state of the art
- An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints
- MOEA/D with Adaptive Weight Adjustment
- Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems
- Improved Metaheuristic Based on the R2 Indicator for Many-Objective Optimization
- Genetic local search for multi-objective combinatorial optimization
- SMS-EMOA: Multiobjective selection based on dominated hypervolume
- Decomposition of a Multiobjective Optimization Problem Into a Number of Simple Multiobjective Subproblems
- A Grid-Based Evolutionary Algorithm for Many-Objective Optimization
- A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization
Cited by
- Efficient Large-Scale Multiobjective Optimization Based on a Competitive Swarm Optimizer
- A Many-Objective Evolutionary Algorithm with Angle-Based Selection and Shift-Based Density Estimation
- A competitive mechanism based multi-objective particle swarm optimizer with fast convergence
- A novel method for multifactorial bio-chemical experiments design based on combinational design theory
- Adaptive Sharing Scheme Based Sub-Swarm Multi-Objective PSO
- Stochastic Computing with Spiking Neural P Systems
- SCM: A method to improve network service layout efficiency with network evolution
- A Novel Multi-objective Evolutionary Algorithm Based on a Further Decomposition Strategy
- 3D fast convex-hull-based evolutionary multiobjective optimization algorithm
- An Interactive Many Objective Evolutionary Algorithm with Cascade Clustering and Reference Point Incremental Learning
- Dynamic reference vectors and biased crossover use for inverse model based evolutionary multi-objective optimization with irregular Pareto fronts
- Fitness partition-based multi-objective differential evolutionary algorithm and its application to the sodium gluconate fermentation process
- An adaptive multi-population differential artificial bee colony algorithm for many-objective service composition in cloud manufacturing
- A Multiobjective Evolutionary Algorithm Based on Coordinate Transformation
- Multiobjective sparse ensemble learning by means of evolutionary algorithms
- Adaptive Sorting-Based Evolutionary Algorithm for Many-Objective Optimization
- Adaptive region adjustment to improve the balance of convergence and diversity in MOEA/D
- A Many-Objective Evolutionary Algorithm With Two Interacting Processes: Cascade Clustering and Reference Point Incremental Learning
- Cooperative Evolutionary Framework With Focused Search for Many-Objective Optimization
- Earthquake prediction model using support vector regressor and hybrid neural networks
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