Showing 1 - 4 of 4
When using representations for genetic algorithms (GAs) every optimization problem canbe separated into a genotype-phenotype and a phenotype-tness mapping. The genotypephenotypemapping is the used representation and the phenotype-tness mapping is the problemthat should be solved.This paper...
Persistent link: https://www.econbiz.de/10005868181
When using gentic and evolutionary algorithms (GEAs) for the optimal communication spanning problem, the design of a suitable tree network encoding is crucial for finding good solutions. The link and node biased (LNB) encoding represents the structure of a tree network using a weighted vector...
Persistent link: https://www.econbiz.de/10005868207
This paper adresses the optimization of telecommunication networks for a multi-period horizon. Four heuristics are presented to cope with the problem to minimize the overall costsfor a network over several periods. For the minimization of cost we use a simple genetic algorithm (GE).[...]
Persistent link: https://www.econbiz.de/10005868210
This paper investigates how the use of redundant representations influences the performance ofgenetic and evolutionary algorithms. Representations are redundant if the number of genotypesexceeds the number of phenotypes. A distinction is made between synonymously and nonsynonymouslyredundant...
Persistent link: https://www.econbiz.de/10005868351