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Genetic Algorithms
Optimizing genetic algorithms for time critical problems

Genetic algorithms have a lot of attributes that makes it a good choice when one needs to solve very complicated problems. The performance of genetic algorithms is a ected by the parameters that are used. Optimization of the parameters for the genetic algorithm is one of the most popular research fields of genetic algorithms. One of the reasons for this is because of the complicated relation between the parameters and factors such as the complexity of the problem. This thesis describes what happens when time is added to this problem. One of the most important parameters is population size and we have found by testing a wide range of problems that the optimal population size is not the same as if time was not involved.
Keywords: Genetic Algorithms, Time Critical, Optimization, Population Size

File: The report (pdf)
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