Dynamic Fuzzy Logic Control of GeneticAlgorithm Probabilities

Genetic algorithms are commonly used to solve combinatorial optimizationproblems. The implementation evolves using genetic operators (crossover, mutation,selection, etc.). Anyway, genetic algorithms like some other methods have parameters(population size, probabilities of crossover and mutation) which need to be tune orchosen.In this paper, our project is based on an existing hybrid genetic algorithmworking on the multiprocessor scheduling problem. We propose a hybrid Fuzzy-Genetic Algorithm (FLGA) approach to solve the multiprocessor scheduling problem.The algorithm consists in adding a fuzzy logic controller to control and tunedynamically different parameters (probabilities of crossover and mutation), in anattempt to improve the algorithm performance. For this purpose, we will design afuzzy logic controller based on fuzzy rules to control the probabilities of crossoverand mutation. Compared with the Standard Genetic Algorithm (SGA), the resultsclearly demonstrate that the FLGA method performs significantly better.

There is something about Mary… and Ted! : Training in mixed-sex groups makes you work harder. A study about the effort when training with the opposite sex.

In many sport associations, regardless of level, women and men rarely practice together. Previous studies indicate that work groups are generally more efficient when there is an even distribution between the sexes. Could that also be the case in sports? This study aims to investigate whether the sex composition of a training group affects the effort and performance of the participants. Eleven volunteers participated in the crossover study consisting of three different 150-meter sprint conditions; individually, single-sex group and mixed-sex group. Sprint times, heart rate and RPE were recorded during all three trials. The result of this study suggests that there might be practical benefits in regards to physical performance and effort to exercise in a training group consisting of both sexes instead of training only with the same-sex or individually. The understanding could be useful in areas such as; training optimisation for both athletes and in patient- and rehabilitation groups, increasing efficiency in work environments, in schools and sports clubs striving for both athletic success and gender equality.