Name
Abstract | ||
|---|---|---|
The Pareto set (PS) of real multi-objective optimization problems (MOPs) are often unknown and complex, so, it is significant for multi-objective evolutionary algorithms (MOEAs) to solve complex PS MOPs (CPS_MOPs namely). In this paper, we combined Latin hypercube sampling (LHS) with MOEA, proposed a LHS based MOEA (LHS-MOEA). We suggested two kinds of LHS-MOEA, in which LHS local search and evolutionary operator are combined to handle CPS_MOPs. Through some experiments, the results demonstrate that LHS-MOEA performs much better than the traditional prevalent MOEA -- NSGA-II in solving CPS_MOPs. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-92137-0_12 | ISICA |
Keywords | Field | DocType |
complex pareto set mops,complex ps mops,evolutionary operator,combine lhs,multi-objective evolutionary algorithm,pareto set,real multi-objective optimization problem,latin hypercube sampling,local search,traditional prevalent moea | Mathematical optimization,Evolutionary algorithm,Computer science,Operator (computer programming),MOPS,Local search (optimization),Optimization problem,Latin hypercube sampling,Pareto principle | Conference |
Volume | ISSN | Citations |
5370 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 11 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinhua Zheng | 1 | 517 | 36.36 |
| Biao Luo | 2 | 554 | 23.80 |
| Miqing Li | 3 | 1055 | 36.73 |
| Jing Li | 4 | 0 | 0.34 |