Name
Abstract | ||
|---|---|---|
Intelligent optimization is a domain of evolutionary computation thatemerges since a few years. All the methods within this discipline are based onmechanisms for maintaining a set of individuals and, separately, a space ofknowledge linked to the individuals. The aim is to make the individuals evolveto reach better solutions generation after generation using the knowledge linkedto them. The idea proposed in this paper consists in using previous experiencesin order to build the knowledge referential and then accelerate the searchprocess. A method which allows reusing knowledge gained from experiencefeedback is proposed. This approach has been applied to the problem ofselection of project scenario in a multi-objective context. An evolutionaryalgorithm has been modified in order to allow the reuse of capitalizedknowledge. This knowledge is gathered in an influence diagram allowing itsreuse by the algorithm. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-79305-2_27 | Artificial Evolution |
Keywords | Field | DocType |
knowledge referential,knowledge linkedto,influence diagram,previous experiencesin order,problem ofselection,evolutionary computation thatemerges,multi-objective context,intelligent optimization,experience feedback approach,project scenario,better solutions generation,evolutionary computing,evolutionary algorithm | Experience feedback,Systems engineering,Software engineering,Evolutionary algorithm,Computer science,Reuse,Evolutionary computation,Influence diagram,Project management | Conference |
Volume | ISSN | ISBN |
4926 | 0302-9743 | 3-540-79304-6 |
Citations | PageRank | References |
1 | 0.37 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paul Pitiot | 1 | 16 | 3.80 |
| Thierry Coudert | 2 | 27 | 7.91 |
| Laurent Geneste | 3 | 107 | 14.82 |
| Claude Baron | 4 | 36 | 12.88 |