Name
Abstract | ||
|---|---|---|
Decomposition via scalarization is a basic concept for multiobjective optimization. The weighted sum (WS) method, a frequently used scalarizing method in decomposition-based evolutionary multiobjective (EMO) algorithms, has good features such as computationally easy and high search efficiency, compared to other scalarizing methods. However, it is often criticized by the loss of effect on nonconvex... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TEVC.2016.2611642 | IEEE Transactions on Evolutionary Computation |
Keywords | Field | DocType |
Pareto optimization,Chebyshev approximation,Evolutionary computation,Search problems,Shape,Benchmark testing | Mathematical optimization,Evolutionary algorithm,A priori and a posteriori,Approximation theory,Evolutionary computation,Multi-objective optimization,Competitive algorithm,Artificial intelligence,Hypercone,Mathematics,Benchmark (computing),Machine learning | Journal |
Volume | Issue | ISSN |
22 | 1 | 1089-778X |
Citations | PageRank | References |
36 | 0.72 | 31 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rui Wang | 1 | 538 | 33.29 |
| Zhongbao Zhou | 2 | 128 | 12.52 |
| Hisao Ishibuchi | 3 | 7385 | 503.41 |
| Tianjun Liao | 4 | 55 | 3.00 |
| Tao Zhang | 5 | 155 | 12.43 |