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 …
A review of evolutionary multimodal multiobjective optimization
R Tanabe, H Ishibuchi - IEEE Transactions on Evolutionary …, 2019 - ieeexplore.ieee.org
Multimodal multiobjective optimization aims to find all Pareto optimal solutions, including
overlapping solutions in the objective space. Multimodal multiobjective optimization has …
overlapping solutions in the objective space. Multimodal multiobjective optimization has …
PlatEMO: A MATLAB platform for evolutionary multi-objective optimization [educational forum]
Over the last three decades, a large number of evolutionary algorithms have been
developed for solving multi-objective optimization problems. However, there lacks an upto …
developed for solving multi-objective optimization problems. However, there lacks an upto …
An indicator-based multiobjective evolutionary algorithm with reference point adaptation for better versatility
During the past two decades, a variety of multiobjective evolutionary algorithms (MOEAs)
have been proposed in the literature. As pointed out in some recent studies, however, the …
have been proposed in the literature. As pointed out in some recent studies, however, the …
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 …
A multiobjective particle swarm optimizer using ring topology for solving multimodal multiobjective problems
This paper presents a new particle swarm optimizer for solving multimodal multiobjective
optimization problems which may have more than one Pareto-optimal solution …
optimization problems which may have more than one Pareto-optimal solution …
A decision variable clustering-based evolutionary algorithm for large-scale many-objective optimization
The current literature of evolutionary many-objective optimization is merely focused on the
scalability to the number of objectives, while little work has considered the scalability to the …
scalability to the number of objectives, while little work has considered the scalability to 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 …
An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints
Having developed multiobjective optimization algorithms using evolutionary optimization
methods and demonstrated their niche on various practical problems involving mostly two …
methods and demonstrated their niche on various practical problems involving mostly two …
A benchmark test suite for evolutionary many-objective optimization
In the real world, it is not uncommon to face an optimization problem with more than three
objectives. Such problems, called many-objective optimization problems (MaOPs), pose …
objectives. Such problems, called many-objective optimization problems (MaOPs), pose …