Name
Abstract | ||
|---|---|---|
In this paper we present a genetic algorithm as an aid for project assignment. The assignment problem illustrated concerns the allocation of projects to students. Students have to choose from a list of possible projects, indicating their preferred choices in advance. Inevitably, some of the more popular projects become 'over-subscribed' and assignment becomes a complex problem. The developed algorithm has compared well to an optimal integer programming approach. One clear advantage of the genetic algorithm is that, by its very nature, we are able to produce a number of feasible project assignments, thus facilitating discussion on the merits of various allocations and supporting multi-objective decision making. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1016/j.cor.2003.11.003 | Computers & OR |
Keywords | Field | DocType |
developed algorithm,feasible project assignment,genetic algorithm,Project assignment,Genetic algorithms,popular project,Multi-objective decision making,project assignment,complex problem,possible project,assignment problem,clear advantage,multi-objective decision,project assignment problem | Mathematical optimization,Assignment problem,Genetic algorithm,Mathematics | Journal |
Volume | Issue | ISSN |
32 | 5 | Computers and Operations Research |
Citations | PageRank | References |
26 | 1.61 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paul R. Harper | 1 | 188 | 18.44 |
| Valter de Senna | 2 | 39 | 4.29 |
| Israel T. Vieira | 3 | 32 | 2.57 |
| Arjan K. Shahani | 4 | 89 | 10.28 |