mgo.tools.metric
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Modification of the crowding distance to avoid infinite values for the first and last point in each domain. The crowding for the second and last element of each domain is instead the distance between the first and second (or last and second but last).
Modification of the crowding distance to avoid infinite values for the first and last point in each domain. The crowding for the second and last element of each domain is instead the distance between the first and second (or last and second but last).
Crowding distance computation see Deb, K., Agrawal, S., Pratap, A. & Meyarivan, T. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. Lecture notes in computer science 1917, 849–858 (2000).
Crowding distance computation see Deb, K., Agrawal, S., Pratap, A. & Meyarivan, T. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. Lecture notes in computer science 1917, 849–858 (2000).
Crowding distance computation see Deb, K., Agrawal, S., Pratap, A. & Meyarivan, T. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. Lecture notes in computer science 1917, 849–858 (2000).
Bader, J., & Zitzler, E. (2011). HypE: An algorithm for fast hypervolume-based many-objective optimization. Evolutionary computation, 19(1), 45-76.
Bader, J., & Zitzler, E. (2011). HypE: An algorithm for fast hypervolume-based many-objective optimization. Evolutionary computation, 19(1), 45-76.
other indic (entropy?) Santos, T., & Xavier, S. (2018). A Convergence Indicator for Multi-Objective Optimisation Algorithms. TEMA (São Carlos), 19(3), 437-448.
Greenhalgh, D., & Marshall, S. (2000). Convergence criteria for genetic algorithms. SIAM Journal on Computing, 30(1), 269-282.
Hypervolume computation based on variant 3 of the algorithm in the paper: C. M. Fonseca, L. Paquete, and M. Lopez-Ibanez. An improved dimension-sweep algorithm for the hypervolume indicator. In IEEE Congress on Evolutionary Computation, pages 1157-1163, Vancouver, Canada, July 2006.
Hypervolume computation based on variant 3 of the algorithm in the paper: C. M. Fonseca, L. Paquete, and M. Lopez-Ibanez. An improved dimension-sweep algorithm for the hypervolume indicator. In IEEE Congress on Evolutionary Computation, pages 1157-1163, Vancouver, Canada, July 2006.
FIXE: The implementation is ugly, as the algorithm as directly been translated from python