Name
Abstract | ||
|---|---|---|
In the paper, a heuristic genetic algorithm for solving resource allocation problems is proposed. The resource allocation problems are to allocate resources to activities so that the fitness becomes as optimal as possible. The objective of this paper is to develop an efficient algorithm to solve resource allocation problems encountered in practice. Various genetic algorithms are studied and a heuristic genetic algorithm is proposed to ameliorate the rate of convergence for resource allocation problems. Simulation results show that the proposed algorithm gives the best performance.
|
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/10.1007/s10115-003-0082-0 | Knowl. Inf. Syst. |
Keywords | Field | DocType |
Genetic algorithm,Heuristics,Optimization problems,Resource allocation problems | Mathematical optimization,Heuristic,Computer science,Heuristics,Resource allocation,Rate of convergence,Population-based incremental learning,Optimization problem,Genetic algorithm | Journal |
Volume | Issue | Citations |
5 | 4 | 13 |
PageRank | References | Authors |
0.95 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zne-Jung Lee | 1 | 940 | 43.45 |
| Shun-Feng Su | 2 | 1194 | 97.62 |
| Chou-Yuan Lee | 3 | 295 | 17.36 |
| Yao-Shan Hung | 4 | 32 | 2.58 |