A genetic local tuning algorithm for a class of combinatorial networks design problems

Author

Sayoud, H. ; Takahashi, K. ; Vaillant, B.

Author_Institution

Fac. of Eng., Multimedia Univ., Cyberjaya, Malaysia

Volume

5

Issue

7

fYear

2001

fDate

7/1/2001 12:00:00 AM

Firstpage

322

Lastpage

324

Abstract

Experimental evidences of many genetic algorithm (GA) researchers is that hybridizing a GA with a local search (LS) heuristic 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 population (IP) composed of the elite and the improved solutions by natural genetic operators is constructed and then a Nelder and Mead (1965) 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.

Keywords

combinatorial mathematics; genetic algorithms; network topology; search problems; telecommunication networks; 20-nodes topology design; GALS mechanism; TDCA problem; capacity assignment problem; combinatorial networks design problems; elite nondominated set of solutions; genetic algorithm; genetic local tuning algorithm; local search heuristic; local search mechanism; natural genetic operators; simplex downhill method; Algorithm design and analysis; Design optimization; Genetic algorithms; Genetic mutations; Optimization methods; Production; Reflection; Robustness; Sampling methods; Topology;

fLanguage

English

Journal_Title

Communications Letters, IEEE

Publisher

ieee

ISSN

1089-7798

Type

jour

DOI

10.1109/4234.935756

Filename

935756