UAV mission planning is one of the core problems in the field of UAV applications. Currently,
mission planning needs to simultaneously optimize multiple conflicting objectives and take …

Since its inception in 2014, the Competitive Swarm Optimizer (CSO) has emerged as a
significant advancement in the field of swarm intelligence, particularly in addressing large …

Robust multi-objective optimization problems (RMOPs) widely exist in real-world
applications, which introduce a variety of uncertainty in optimization models. While some …

Large-scale multiobjective optimization problems (LSMOPs) pose a great challenge to
maintaining the diversity of solutions. However, existing large-scale multiobjective …

Sparse multi-objective optimization problems (SMOPs) are prevalent in a wide range of
applications, spanning from the fields of science to engineering. Existing sparse …

When tackling large-scale multi-objective problems (LSMOPs), the computational budget
could be wasted by traditional offspring generators that explore the search space in a nearly …

Weighted optimization framework (WOF) achieves variable dimensionality reduction by
grouping variables and optimizing weights, playing an important role in large-scale multi …

In the domain of machine learning, feature selection plays a pivotal role in enhancing model
performance, especially for imbalanced datasets, where traditional methods often fall short …

Abstract Solving Large-Scale Multi-Objective Optimization Problems (LSMOPs) is the major
challenge in evolution computation. Due to the large number of decision variables involved …

Competitive swarm optimizer (CSO) based on multidirectional search plays a crucial role in
addressing large-scale multiobjective optimization problems (LSMOPs). However, relying …