Understanding knee points in bicriteria problems and their implications as preferred solution principles
By Kalyanmoy Deb, Shivam Gupta. 2011
281 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Control and Systems Engineering, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/fc09acf13170776f840959265d4979f1a100cc85
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In Computational Theory and Mathematics
In Control and Systems Engineering
In Management Science and Operations Research
Citations in the corpus
- A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization (2015, unknown): “NSGA-II [6] and SPEA2 [7] are two representative Pareto-based MOEAs, which have been shown to be very effective in solving MOPs having two or three objectives.”
- Benchmark Problems and Performance Indicators for Search of Knee Points in Multiobjective Optimization (2020, methodology): “Generally speaking, knee points, edge-knee points, extreme points, and robust solutions [39], [51] are solutions generically preferred by users.”
- A Method for a Posteriori Identification of Knee Points Based on Solution Density (2018, background): “The reflex/bend angle [26], [27] describes knee points with the largest reflex angle, and a variant proposed by Deb and Gupta [22] slightly modifies the description of the bend angle by giving a pair of values (α > 1, β > 1).”