Autor: |
Miettinen, Kaisa, Ruiz, Francisco |
Předmět: |
|
Zdroj: |
Journal of Global Optimization; Sep2019, Vol. 75 Issue 1, p1-2, 2p |
Abstrakt: |
Many real optimization applications deal with making decisions in the presence of several conflicting objectives and different methodologies have been developed to solve these so-called multiobjective optimization problems. In the article "Efficient Computation of Expected Hypervolume Improvement Using Box Decomposition Algorithms", Kaifeng Yang, Michael Emmerich, Andre Deutz and Thomas Bäck concentrate on multiobjective Bayesian global optimization. In this article, named "Nonmonotone Line Searches for Unconstrained Multiobjective Optimization Problems", Kanako Mita, Ellen Hidemi Fukuda and Nobuo Yamashita consider two types of nonmonotone line searches for descent methods and propose a new nonmonotone technique specifically for multiobjective optimization problems. [Extracted from the article] |
Databáze: |
Complementary Index |
Externí odkaz: |
|