Name
Abstract | ||
|---|---|---|
A multi-agent genetic algorithm is proposed to solve single-mode resource constrained project scheduling problems (MAGA-RCPSPs). In MAGA-RCPSPs, an agent represents a candidate solution to the RCPSP, and all agents live in a latticelike environment, with each agent fixed on a lattice point. In the experiments, benchmark problems Patterson and J30 are used. The results show that MAGA-RCPSPs has a good performance. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2464576.2464667 | GECCO (Companion) |
Keywords | Field | DocType |
candidate solution,latticelike environment,multi-agent genetic algorithm,good performance,lattice point,single-mode resource,benchmark problem,project scheduling problem,genetic algorithms,multi agent systems | Mathematical optimization,Schedule (project management),Fair-share scheduling,Computer science,Multi-agent system,Genetic algorithm scheduling,Genetic algorithm,Distributed computing | Conference |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoxiao Yuan | 1 | 0 | 0.68 |
| Chuanfu Xiao | 2 | 0 | 0.34 |
| Xiyu Lv | 3 | 0 | 0.34 |
| Jing Liu | 4 | 1043 | 115.54 |