Evolutionary Algorithms for Multi-Objective Optimization: Performance Assessments and Comparisons

By Kay Chen Tan, Tong-heng Lee, Eik Fun Khor. Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546), 2001

323 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Civil and Structural Engineering, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/d27ca7b4fa729b5611e1e34204c6e53c9343cbac

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. Liang Feng
2. Yew-Soon Ong
3. Zesong Fei
4. Lajos Hanzo
5. Shaoshi Yang
6. Bin Li
7. Chengwen Xing
8. Jie Zhang

In Civil and Structural Engineering

1. Lajos Hanzo

In Computational Theory and Mathematics

1. Liang Feng
2. Yew-Soon Ong
3. Zesong Fei
4. Lajos Hanzo
5. Shaoshi Yang
6. Bin Li
7. Chengwen Xing
8. Jie Zhang

Citations in the corpus

• Consistencies and Contradictions of Performance Metrics in Multiobjective Optimization (2014, background): “[48] proposed the parameter dependent metric UD as follows:”
• Performance indicators in multiobjective optimization (2018, unknown): “The authors of [40] introduce the Uniform distribution indicator, based too on the search of niches of size σ, given by UD(S, σ) = 1 1 +Dnc(S, σ)”
• A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems (2016, background): “MOEAs aim for finding a set of representative Pareto-optimal solutions in a single run [14], [19], [20].”