Kriging-based infill sampling criterion for constraint handling in multi-objective optimization

2015 ◽  
Vol 64 (1) ◽  
pp. 97-115 ◽  
Author(s):  
Jesús Martínez-Frutos ◽  
David Herrero-Pérez
Keyword(s):  
Constraint Handling ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Infill Sampling

scholarly journals Localized probability of improvement for kriging based multi-objective optimization

Open Physics ◽  
2017 ◽  
Vol 15 (1) ◽  
pp. 954-958
Author(s):  
Yinjiang Li ◽  
Song Xiao ◽  
Paolo Di Barba ◽  
Mihai Rotaru ◽  
Jan K. Sykulski
Keyword(s):  
Uniform Distribution ◽  
Nearest Neighbor ◽  
Higher Dimensions ◽  
Multi Objective Optimization ◽  
New Approach ◽  
Multi Objective ◽  
Local Probability ◽  
Pareto Fronts ◽  
Probability Of Improvement ◽  
Infill Sampling

AbstractThe paper introduces a new approach to kriging based multi-objective optimization by utilizing a local probability of improvement as the infill sampling criterion and the nearest neighbor check to ensure diversification and uniform distribution of Pareto fronts. The proposed method is computationally fast and linearly scalable to higher dimensions.

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