Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
On the State of Evolutionary Computation
Proceedings of the 5th International Conference on Genetic Algorithms
How to Solve It: Modern Heuristics
How to Solve It: Modern Heuristics
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
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In this work, alternative voting methods are compared to determine NASCAR rankings for the Sprint Cup Series. All of these methods make use only of the final placement of each driver in each race. We then construct a set of metrics to determine the effectiveness of each of these voting methods when compared to one another and the actual NASCAR scoring system. Finally, we attempt to generate a more optimal method, as defined by those same metrics, using a real-coded genetic algorithm. Our results show that most of the alternative voting methods vastly outperform the actual NASCAR system. Likewise, the method produced by the genetic algorithm outperforms even the best of the alternative methods.