A fast and elitist multiobjective genetic algorithm¶
Deb, K., Pratap, Agarwal, & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182-197.
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Primes¶
- Multiobjective Optimization
- The mature multiobjective-optimization field emerged over 1960s-1980s with development of scalarization methods (Charnes-Cooper goal programming 1961; Haimes ε-constraint 1971), evolutionary approaches (Schaffer 1985 for the Vector Evaluated Genetic Algorithm, Goldberg 1989, with Deb, Pratap, Agarwal, and Meyarivan (2002) introducing the NSGA-II algorithm that became the field's modern workhorse), and interactive methods (Geoffrion-Dyer-Feinberg 1972, STEM method by Benayoun et al. 1971).
This sourceIntroduces NSGA-II, the dominant evolutionary MOO algorithm of the 2000s-2010s; combines fast non-dominated sorting, elitism, and crowding distance.
- The mature multiobjective-optimization field emerged over 1960s-1980s with development of scalarization methods (Charnes-Cooper goal programming 1961; Haimes ε-constraint 1971), evolutionary approaches (Schaffer 1985 for the Vector Evaluated Genetic Algorithm, Goldberg 1989, with Deb, Pratap, Agarwal, and Meyarivan (2002) introducing the NSGA-II algorithm that became the field's modern workhorse), and interactive methods (Geoffrion-Dyer-Feinberg 1972, STEM method by Benayoun et al. 1971).
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