Using a Gradient Based Method to Seed an EMO Algorithm.
Alfredo García Hernández-DíazCarlos A. Coello CoelloFatima PerezRafael CaballeroJulián MolinaPublished in: MCDM (2008)
Keyphrases
- computational cost
- dynamic programming
- significant improvement
- cost function
- improved algorithm
- high accuracy
- optimization algorithm
- computational complexity
- preprocessing
- experimental evaluation
- theoretical analysis
- detection method
- detection algorithm
- similarity measure
- energy function
- classification method
- convergence rate
- experimental study
- objective function
- estimation algorithm
- support vector machine svm
- optimization method
- segmentation method
- computationally efficient
- synthetic and real images
- computational efficiency
- single pass
- pairwise
- segmentation algorithm
- prior information
- high efficiency
- recognition algorithm
- noisy data
- learning algorithm
- matching algorithm
- k means
- mathematical model
- selection algorithm
- tree structure
- classification algorithm
- optimal solution
- benchmark problems
- input data
- clustering method
- simulated annealing
- np hard
- image matching
- reconstruction method
- lower bound
- graph cuts
- seed selection
- test problems
- solution quality
- knapsack problem
- region of interest