Surrogate-Assisted Cooperative Swarm Optimization of High-Dimensional Expensive Problems

By Chaoli Sun, Yaochu Jin, Ran Cheng, Jinliang Ding, J. Zeng. IEEE Transactions on Evolutionary Computation, 2017

363 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/aa9d4403443abe31b7c828ee6df0b21c155f3dfd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Yaochu Jin
2. Swagatam Das
3. Ali Asghar Heidari
4. Seyedali Mirjalili
5. Ponnuthurai Nagaratnam Suganthan
6. Xin-She Yang
7. Handing Wang
8. Huiling Chen

In Computational Theory and Mathematics

1. Yaochu Jin
2. Swagatam Das
3. Handing Wang
4. Xin-She Yang
5. Ponnuthurai Nagaratnam Suganthan
6. Ali Asghar Heidari
7. Seyedali Mirjalili
8. Huiling Chen

Citations in the corpus

• A Random Forest-Assisted Evolutionary Algorithm for Data-Driven Constrained Multiobjective Combinatorial Optimization of Trauma Systems (2020, background): “SAEAs for single-objective optimization [6], [25], [29], [30]; multiobjective optimization [12], [22], [31], [32]; and manyobjective optimization [13], [33] have been proposed.”
• Committee-Based Active Learning for Surrogate-Assisted Particle Swarm Optimization of Expensive Problems (2017, background): “So far most SAEAs have been developed to tackle small to medium-sized (up to 30 decision variables) expensive optimization problems with few exceptions [29], [30], [31], [32], partly because a majority of real-world expensive optimization problems have a medium-sized decision variables [11], and”
• Bio-inspired computation: Where we stand and what's next (2019, methodology): “Sophisticated evolutionary methods are receiving attention in recent years, such as cooperative PSOs [200], hierarchical PSOs [205] or Cooperative Co-evolutionary approaches [206].”
• Offline Data-Driven Evolutionary Optimization Using Selective Surrogate Ensembles (2019, methodology): “3) Surrogate-assisted cooperative swarm optimization algo-rithm (SA-COSO) [28].”
• Data-Driven Evolutionary Optimization: An Overview and Case Studies (2019, methodology): “Some on-line optimization algorithms, e.g., K-RVEA [11, 13], CSEA [74], and SL-PSO [88] have been proposed to tackle these challenges.”
• INFO: An efficient optimization algorithm based on weighted mean of vectors (2022, background): “Currently, PSO has taken its place in the fields of large-scale optimisation problems[19], feature selection[20], single-objective optimization problem[21], multiobjective optimisation problems[22], and high-dimensional expensive problem[23].”