Since its inception in 1995, Differential Evolution (DE) has emerged as one of the most
frequently used algorithms for solving complex optimization problems. Its flexibility and …

Both objective optimization and constraint satisfaction are crucial for solving constrained
multiobjective optimization problems, but the existing evolutionary algorithms encounter …

Green scheduling in the manufacturing industry has attracted increasing attention in
academic research and industrial applications with a focus on energy saving. As a typical …

Niching techniques have been widely incorporated into evolutionary algorithms (EAs) for
solving multimodal optimization problems (MMOPs). However, most of the existing niching …

When solving constrained optimization problems (COPs) by evolutionary algorithms, the
search algorithm plays a crucial role. In general, we expect that the search algorithm has the …

This study aims to investigate the effects of winding angles (25°, 50°, 75°, 90°; the 0°
winding angle is along the axial direction of the tube) and thicknesses (3-ply, 6-ply, 9-ply) on …

Most current evolutionary multi-objective optimization (EMO) algorithms perform well on
multi-objective optimization problems without constraints, but they encounter difficulties in …

This paper studies an unmanned aerial vehicle (UAV)-assisted Internet of Things (IoT) data
collection system, where a UAV is employed as a data collection platform for a group of …

Bio-inspired cellular structures provide excellent elements and design concepts for
designing thin-walled energy-absorbing structures of vehicles, trains and aircrafts, due to …

Constrained multi-objective optimization problems (CMOPs) are common in real-world
engineering application, and are difficult to solve because of the conflicting nature of the …