A reinforcement learning hyper-heuristic in multi-objective optimization with application to structural damage identification

Keyphrases

• Multi-objective Optimization 100%
• Structural Damage Detection 100%
• Reinforcement Learning 100%
• Hyper-heuristics 100%
• Search Algorithm 33%
• Solution Technique 33%
• Solution Set 33%
• Multiple Solutions 33%
• Damage Scenarios 33%
• Single Point 33%
• Robust Performance 33%
• Heuristic Scheme 33%
• Non-dominated Sorting Genetic Algorithm (NSGA-II) 33%
• Multiple Decision Criteria 33%
• Hypervolume 33%
• Benchmark Test Cases 33%
• Crowding Distance 33%
• Multi-objective Simulated Annealing 33%
• Archived multiobjective Simulated Annealing (AMOSA) 33%
• Diversity of Solutions 33%
• Low-level Heuristics 33%
• Point Search 33%

Computer Science

• Reinforcement Learning 100%
• Multi-Objective Optimization 100%
• Hyper-Heuristic 100%
• Structural Damage 100%
• Multiobjective 33%
• Searching Algorithm 33%
• Quality Solution 33%
• Non-Dominated Sorting Genetic Algorithm II 33%
• Decision Criterion 33%
• Simulated Annealing 33%
• Research Subject 33%
• Crowding Distance 33%

Engineering

• Multiobjective Optimization 100%
• Structural Damage Identification 100%
• Reinforcement Learning 100%
• Solution Technique 33%
• Simulated Annealing Algorithm 33%
• Search Algorithm 33%
• Research Subject 33%
• Damage Scenario 33%
• Non-Dominated Sorting Genetic Algorithm II 33%
• Decision Criterion 33%
• Crowding Distance 33%