Many-objective evolutionary algorithms: A survey
Multiobjective evolutionary algorithms (MOEAs) have been widely used in real-world
applications. However, most MOEAs based on Pareto-dominance handle many-objective …
applications. However, most MOEAs based on Pareto-dominance handle many-objective …
Performance indicators in multiobjective optimization
In recent years, the development of new algorithms for multiobjective optimization has
considerably grown. A large number of performance indicators has been introduced to …
considerably grown. A large number of performance indicators has been introduced to …
A reference vector guided evolutionary algorithm for many-objective optimization
In evolutionary multiobjective optimization, maintaining a good balance between
convergence and diversity is particularly crucial to the performance of the evolutionary …
convergence and diversity is particularly crucial to the performance of the evolutionary …
An evolutionary many-objective optimization algorithm based on dominance and decomposition
Achieving balance between convergence and diversity is a key issue in evolutionary
multiobjective optimization. Most existing methodologies, which have demonstrated their …
multiobjective optimization. Most existing methodologies, which have demonstrated their …
A survey on the hypervolume indicator in evolutionary multiobjective optimization
Hypervolume is widely used as a performance indicator in the field of evolutionary
multiobjective optimization (EMO). It is used not only for performance evaluation of EMO …
multiobjective optimization (EMO). It is used not only for performance evaluation of EMO …
A new dominance relation-based evolutionary algorithm for many-objective optimization
Many-objective optimization has posed a great challenge to the classical Pareto dominance-
based multiobjective evolutionary algorithms (MOEAs). In this paper, an evolutionary …
based multiobjective evolutionary algorithms (MOEAs). In this paper, an evolutionary …
Quality evaluation of solution sets in multiobjective optimisation: A survey
M Li, X Yao - ACM Computing Surveys (CSUR), 2019 - dl.acm.org
Complexity and variety of modern multiobjective optimisation problems result in the
emergence of numerous search techniques, from traditional mathematical programming to …
emergence of numerous search techniques, from traditional mathematical programming to …
IGD indicator-based evolutionary algorithm for many-objective optimization problems
Inverted generational distance (IGD) has been widely considered as a reliable performance
indicator to concurrently quantify the convergence and diversity of multiobjective and many …
indicator to concurrently quantify the convergence and diversity of multiobjective and many …
A surrogate-assisted reference vector guided evolutionary algorithm for computationally expensive many-objective optimization
We propose a surrogate-assisted reference vector guided evolutionary algorithm (EA) for
computationally expensive optimization problems with more than three objectives. The …
computationally expensive optimization problems with more than three objectives. The …
Performance of decomposition-based many-objective algorithms strongly depends on Pareto front shapes
H Ishibuchi, Y Setoguchi, H Masuda… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Recently, a number of high performance many-objective evolutionary algorithms with
systematically generated weight vectors have been proposed in the literature. Those …
systematically generated weight vectors have been proposed in the literature. Those …