Name
Abstract | ||
|---|---|---|
Before Multiobjective Evolutionary Algorithms (MOEAs) can be used as a widespread tool for solving arbitrary real world problems there are some salient issues which require further investigation. One of these issues is how a uniform distribution of solutions along the Pareto non-dominated front can be obtained for badly scaled objective functions. This is especially a problem if the bounds for the objective functions are unknown, which may result in the non- dominated solutions found by the MOEA to be biased towards one objective, thus resulting in a less diverse set of tradeofis. In this paper, the issue of obtaining a diverse set of solutions for badly scaled objective functions will be investigated and the proposed solutions will be implemented using the NSGA-II algorithm. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-24855-2_2 | GECCO (2) |
Keywords | Field | DocType |
uniform distribution,objective function | Mathematical optimization,Evolutionary algorithm,Computer science,Uniform distribution (continuous),Multi-objective optimization,Scaling,Genetic algorithm,Pareto principle,Salient | Conference |
Citations | PageRank | References |
3 | 0.53 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gerulf K. M. Pedersen | 1 | 8 | 1.28 |
| David E. Goldberg | 2 | 5790 | 940.53 |