Results 181 to 190 of about 1,756,488 (218)

Hypervolume Sharpe-Ratio Indicator: Formalization and First Theoretical Results

2016
Set-quality indicators have been used in Evolutionary Multiobjective Optimization Algorithms (EMOAs) to guide the search process. A new class of set-quality indicators, the Sharpe-Ratio Indicator, combining the selection of solutions with fitness assignment has been recently proposed.
Andreia P. Guerreiro, Carlos M. Fonseca
openaire   +1 more source

Tight Bounds for the Approximation Ratio of the Hypervolume Indicator

2010
The hypervolume indicator is widely used to guide the search and to evaluate the performance of evolutionary multi-objective optimization algorithms. It measures the volume of the dominated portion of the objective space which is considered to give a good approximation of the Pareto front.
Bringmann, K. ; https://orcid.org/0000-0003-1356-5177, Friedrich, T.   +1 more
openaire   +3 more sources

Scaling up indicator-based MOEAs by approximating the least hypervolume contributor

Proceedings of the 12th annual conference companion on Genetic and evolutionary computation, 2010
It is known that the performance of multi-objective evolutionary algorithms (MOEAs) in general deteriorates with increasing number of objectives. For few objectives, MOEAs relying on the contributing hypervolume as (second-level) sorting criterion are the methods of choice.
Thomas Voß, Tobias Friedrich, Karl Bringmann, Christian Igel   +3 more
openaire   +1 more source

Indicator-based evolutionary algorithm with hypervolume approximation by achievement scalarizing functions

Proceedings of the 12th annual conference on Genetic and evolutionary computation, 2010
Pareto dominance-based algorithms have been the main stream in the field of evolutionary multiobjective optimization (EMO) for the last two decades. It is, however, well-known that Pareto-dominance-based algorithms do not always work well on many-objective problems with more than three objectives. Currently alternative frameworks are studied in the EMO
Hisao Ishibuchi, Noritaka Tsukamoto, Yuji Sakane, Yusuke Nojima   +3 more
openaire   +1 more source

A novel hybrid hypervolume indicator and reference vector adaptation strategies based evolutionary algorithm for many-objective optimization

Engineering computations, 2020
Gaurav Dhiman, Mukesh Soni, Hari Mohan Pandey, A. Słowik, Harsimranjit Kaur   +4 more
semanticscholar   +1 more source

Constraint handling with modified hypervolume indicator for multi-objective optimization problems

Proceedings of the 12th annual conference companion on Genetic and evolutionary computation, 2010
Many problems across various domains of research may be formulated as a multi-objective optimization problem. The Multi-objective Evolutionary Algorithm framework (MOEA) has been applied successfully to unconstrained multi-objective optimization problems.
openaire   +1 more source

Indicator displacement assays (IDAs): the past, present and future

Chemical Society Reviews, 2021
Adam Charles Sedgwick, James T Brewster, Tianhong Wu   +2 more
exaly  

Cooperativeness Measure Based on the Hypervolume Indicator and Matching Method for Concurrent Negotiations

, 2020
Ryohei Kawata, K. Fujita
semanticscholar   +1 more source

Indicator-based Multi-objective Evolutionary Algorithms

ACM Computing Surveys, 2021
Jesús Guillermo Falcón-Cardona, Carlos A Coello Coello   +1 more
exaly  

The Hypervolume Indicator

ACM Computing Surveys, 2022
Andreia P Guerreiro, Carlos M Fonseca, Luís Paquete   +2 more
exaly