[HTML][HTML] Large-scale evolutionary optimization: A review and comparative study
Large-scale global optimization (LSGO) problems have widely appeared in various real-
world applications. However, their inherent complexity, coupled with the curse of …
world applications. However, their inherent complexity, coupled with the curse of …
A two-stage cooperative evolutionary algorithm with problem-specific knowledge for energy-efficient scheduling of no-wait flow-shop problem
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 …
academic research and industrial applications with a focus on energy saving. As a typical …
A greedy cooperative co-evolutionary algorithm with problem-specific knowledge for multiobjective flowshop group scheduling problems
The flowshop sequence-dependent group scheduling problem (FSDGSP) with the
production efficiency measures has been extensively studied due to its wide industrial …
production efficiency measures has been extensively studied due to its wide industrial …
A classifier-assisted level-based learning swarm optimizer for expensive optimization
Surrogate-assisted evolutionary algorithms (SAEAs) have become one popular method to
solve complex and computationally expensive optimization problems. However, most …
solve complex and computationally expensive optimization problems. However, most …
Dual differential grou**: A more general decomposition method for large-scale optimization
Cooperative coevolution (CC) algorithms based on variable decomposition methods are
efficient in solving large-scale optimization problems (LSOPs). However, many …
efficient in solving large-scale optimization problems (LSOPs). However, many …
A comprehensive competitive swarm optimizer for large-scale multiobjective optimization
Competitive swarm optimizers (CSOs) have shown very promising search efficiency in large-
scale decision space. However, they face difficulties when solving large-scale multi-/many …
scale decision space. However, they face difficulties when solving large-scale multi-/many …
A distributed swarm optimizer with adaptive communication for large-scale optimization
Large-scale optimization with high dimensionality and high computational cost becomes
ubiquitous nowadays. To tackle such challenging problems efficiently, devising distributed …
ubiquitous nowadays. To tackle such challenging problems efficiently, devising distributed …
Swarm intelligence research: From bio-inspired single-population swarm intelligence to human-machine hybrid swarm intelligence
GY Wang, DD Cheng, DY **a, HH Jiang - Machine Intelligence Research, 2023 - Springer
Swarm intelligence has become a hot research field of artificial intelligence. Considering the
importance of swarm intelligence for the future development of artificial intelligence, we …
importance of swarm intelligence for the future development of artificial intelligence, we …
Multiple-strategy learning particle swarm optimization for large-scale optimization problems
H Wang, M Liang, C Sun, G Zhang, L **e - Complex & Intelligent Systems, 2021 - Springer
The balance between the exploration and the exploitation plays a significant role in the meta-
heuristic algorithms, especially when they are used to solve large-scale optimization …
heuristic algorithms, especially when they are used to solve large-scale optimization …
Cooperative co-evolution for large-scale multi-objective air traffic flow management
Air traffic flow management (ATFM) is the key driver of efficient aviation. It aims at balancing
traffic demand against airspace capacity by scheduling aircraft, which is critical for air …
traffic demand against airspace capacity by scheduling aircraft, which is critical for air …