A hybrid evolutionary approach to the nurse rostering problem

Keyphrases

• Genetic Algorithm 100%
• Stochastic Ranking 100%
• Hybrid Evolutionary Algorithm 100%
• Nurse Rostering Problem 100%
• Algorithm Framework 66%
• Hybrid Algorithm 66%
• Hyper-heuristics 66%
• Simulated Annealing 66%
• Ranking Method 66%
• Superior Performance 33%
• Feasible Solution 33%
• Local Search Algorithm 33%
• Computational Results 33%
• Constraint Handling Technique 33%
• Benchmark Problems 33%
• Penalty Method 33%
• Search Problems 33%
• Optimization Benchmark 33%
• Nurse Rostering 33%
• Constrained Optimization 33%

Computer Science

• Genetic Algorithm 100%
• Evolutionary Approach 100%
• Hybrid Algorithm 66%
• Hyper-Heuristic 66%
• Simulated Annealing 66%
• Superior Performance 33%
• Feasible Solution 33%
• Local Search Algorithm 33%
• Objective Function 33%
• Penalty Function Method 33%
• Benchmark Problem 33%
• Handling Technique 33%
• Constrained Optimization 33%

Mathematics

• Stochastics 100%
• Genetic Algorithm 100%
• Objective Function 33%
• Feasible Solution 33%
• Local Search 33%
• Search Algorithm 33%
• Constrained Optimization 33%