Name
Title | ||
|---|---|---|
A genetic local tuning algorithm for a class of combinatorial networks design problems |
Abstract | ||
|---|---|---|
Abstract—Experimental evidences of many,genetic algorithm researchers is that hybridizing a GA with a local search (LS) heuristics is beneficial. It combines the ability of the GA to widely sample a search space with a local search Hill-Climbing ability. This letter presents a genetic local search (GALS) mechanism applied on two stages on the initial genetic population. An elite nondominated set of solutions is selected, an intermediate popu- lation (IP) composed,of the elite and the improved solutions by natural genetic operators is constructed and then a Nelder and Mead simplex downhill method (SDM) is applied to some solutions of the IP. Experimental results from solving a 20-nodes topology design and capacity assignment (TDCA) problem suggest that our approach provides superior results compared to four simple GA implementations found in the literature. Index Terms—Capacity assignment, combinatorial optimiza- tion, genetic algorithms, local search, topology design. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/4234.935756 | IEEE Communications Letters |
Keywords | Field | DocType |
Algorithm design and analysis,Reflection,Genetic algorithms,Topology,Design optimization,Robustness,Production,Genetic mutations,Optimization methods,Sampling methods | Population,Heuristic,Mathematical optimization,Search algorithm,Telecommunications network,Computer science,Algorithm,Network topology,Combinatorial optimization,Local search (optimization),Genetic algorithm | Journal |
Volume | Issue | ISSN |
5 | 7 | 1089-7798 |
Citations | PageRank | References |
1 | 0.35 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| H. Sayoud | 1 | 1 | 0.35 |
| K. Takahashi | 2 | 14 | 2.84 |
| B. Vaillant | 3 | 1 | 0.35 |