A new approach to target region based multiobjective evolutionary algorithms

Keyphrases

• Many-objective Evolutionary Algorithm (MaOEA) 100%
• Region-based 100%
• Pareto Optimal Solution 100%
• Non-dominated Sorting Genetic Algorithm (NSGA-II) 66%
• Algorithm Framework 66%
• Multi-target 66%
• Preference Information 66%
• SMS-EMOA 66%
• Benchmark Problems 33%
• Decision Maker 33%
• Information-centric 33%
• Pareto Front 33%
• Process Optimization 33%
• Discrete-continuous 33%
• Hypervolume Indicator 33%
• Well-distributed 33%
• Preferred Region 33%
• Ranking Criteria 33%
• Discrete Problem 33%
• Chebyshev Distance 33%
• Continuous Problems 33%
• Region Information 33%
• Crowding Distance 33%
• Real Interests 33%
• Non-dominated Sorting 33%
• Adequate Set 33%
• Coordinate Spaces 33%
• Coordinate Transformation 33%
• Point Target 33%
• Spherical Target 33%
• Improved Algorithm 33%
• R2 Indicator 33%
• Fine-grained Resolution 33%
• Rectangular Target 33%

Computer Science

• multi-objective evolutionary algorithm 100%
• Non-Dominated Sorting Genetic Algorithm II 66%
• Pareto Optimal Solution 66%
• Benchmark Problem 33%
• Decision Maker 33%
• Experimental Result 33%
• Chebyshev Distance 33%
• Pareto-optimality 33%
• Coordinate Transformation 33%
• Crowding Distance 33%
• Space Coordinate 33%