Grid-Enabled Mutation-Based Genetic Algorithm to Optimise Nuclear Fusion Devices

Fusion community is becoming more important as long as fusion energy is considered the next generation of energy. However, many problems are presented in fusion devices. One of these problems consists of improving the equilibrium of confined plasma. Some modelling tools can be used to improve the equilibrium, but the computational cost of these tools and the number of different configurations to simulate make impossible to perform the required tests to obtain optimal designs. With grid computing we have the computational resources needed for running all these tests and with genetic algorithms (GAs) we can look for an approximate result without exploring all the solution space. This work joins all these ideas. The obtained results are very encouraging.

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