README.md

In lucasmpavelski/metaOpt: Meta-Learning for Optimization

Meta-leaning for Optimization

This package contains the main steps for using meta-learning for optimization, as described in the following papers:

• PAVELSKI, LUCAS MARCONDES; DELGADO, MYRIAM REGATTIERI ; KESSACI, MARIE-ÉLÉONORE . Meta-learning on flowshop using fitness landscape analysis. In: the Genetic and Evolutionary Computation Conference, 2019, Prague. Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '19. New York: ACM Press, 2019. p. 925.
• PAVELSKI, LUCAS; DELGADO, MYRIAM ; KESSACI, MARIE-ELEONORE . Meta-Learning for Optimization: A Case Study on the Flowshop Problem Using Decision Trees. In: 2018 IEEE Congress on Evolutionary Computation (CEC), 2018, Rio de Janeiro. 2018 IEEE Congress on Evolutionary Computation (CEC), 2018. p. 1.
• PAVELSKI, LUCAS MARCONDES; KESSACI, MARIE-ELEONORE ; DELGADO, MYRIAM REGATTIERI . Recommending Meta-Heuristics and Configurations for the Flowshop Problem via Meta-Learning: Analysis and Design. In: 2018 7th Brazilian Conference on Intelligent Systems (BRACIS), 2018, Sao Paulo. 2018 7th Brazilian Conference on Intelligent Systems (BRACIS), 2018. p. 163.

lucasmpavelski/metaOpt documentation built on Aug. 23, 2021, 12:03 p.m.