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The main goal of this paper is to summarize the previous research on parallel genetic algo rithms We present an extension to previous categorizations of the parallelization techniques used in this eld We will use this categorization to guide us through a review of many of the most important publications We will build on this survey to try to identify some(More)
Data from a population-based case-control study conducted in Adelaide, South Australia, and involving 451 case-control pairs, were analysed to determine whether the associations of menstrual, reproductive, dietary and other factors with risk of breast cancer differed by oestrogen receptor (ER) status. Data on ER status were available for 380 cases. The(More)
This paper presents models that predict the speedup of two cases that bound the possible topologies and migration rates of parallel genetic algorithms (GAs). The rst bounding case is a parallel GA with completely isolated demes or subpopulations and for this case the model and the experiments show that the speedup is not very signiicant when more demes are(More)
Implementations of parallel genetic algorithms (GAs) with multiple populations are common , but they introduce several parameters whose eeect on the quality of the search is not well understood. Parameters such as the number of populations, their size, the topology of communications, and the migration rate have to be set carefully to reach adequate(More)
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use better algorithms and more eecient implementations to reach good solutions fast. This chapter describes the implementation of master-slave and multiple-population parallel GAs. The goal of the chapter is to help others to implement their own parallel codes. To(More)