Estudio de evolución y maduración del ciruelo japonés mediante análisis hiperespectral y sistemas inteligentes. 

Proyecto IB16035.

In the quest for Energy Efficient Genetic Algorithms

In the quest for Energy Efficient Genetic Algorithms

 

Although usually quality of solutions and running time are the main features of algorithms, recently a new trend in computer science tries to contextualize these features under a new perspective: power consumption. This paper presents a preliminary analysis of the standard genetic algorithm, using two well-known benchmark problems, considering power consumption when battery-powered devices are used to run them. Results show that some of the main parameters of the algorithm has an impact on instantaneous energy consumption -that departs from the expected behavior, and therefore on the amount of energy required to run the algorithm. Although we are still far from finding the way to design energy-efficient EAs, we think the results open up a new perspective that will allow us to achieve this goal in the future. 

 

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