A Large-Scale Combinatorial Many-Objective Evolutionary Algorithm for Intensi…

Intensity-modulated radiotherapy (IMRT) is one of the most popular techniques for cancer treatment. However, existing IMRT planning methods can only generate one solution at a time and, consequentl…

Hierarchy Ranking Method for Multimodal Multiobjective Optimization With Loca…

Multimodal multiobjective problems (MMOPs) commonly arise in real-world situations where distant solutions in decision space share a very similar objective value. Traditional multimodal multiobject…

A Coevolutionary Framework for Constrained Multiobjective Optimization Problems

Constrained multiobjective optimization problems (CMOPs) are challenging because of the difficulty in handling both multiple objectives and constraints. While some evolutionary algorithms have demo…

An Evolutionary Multitasking Method for Multiclass Classification [Research F…

As an important research topic of machine learning, multiclass classification has wide applications ranging from computer vision to bioinformatics. A variety of multiclass classification algorithms…

Comparing the Performance of Evolutionary Algorithms for Sparse Multi-Objecti…

Many real-world multi-objective optimization problems (MOPs) are characterized by a large number of decision variables, where the decision variables are mostly set to zero in the Pareto optimal sol…

Paired Offspring Generation for Constrained Large-Scale Multiobjective Optimi…

Constrained multiobjective optimization problems (CMOPs) widely exist in real-world applications, and they are challenging for conventional evolutionary algorithms (EAs) due to the existence of mul…

A Multipopulation Evolutionary Algorithm for Solving Large-Scale Multimodal M…

Multimodal multiobjective optimization problems (MMOPs) widely exist in real-world applications, which have multiple equivalent Pareto-optimal solutions that are similar in the objective space but …

An Evolutionary Algorithm for Large-Scale Sparse Multiobjective Optimization …

In the last two decades, a variety of different types of multiobjective optimization problems (MOPs) have been extensively investigated in the evolutionary computation community. However, most exis…

Accelerating Large-Scale Multiobjective Optimization via Problem Reformulation

In this paper, we propose a framework to accelerate the computational efficiency of evolutionary algorithms on large-scale multiobjective optimization. The main idea is to track the Pareto optimal …

A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization