Abstract
Team pursuit track cycling is a bicycle racing sport held on velodromes and it is part of the Summer Olympics. It involves the use of strategies to minimize the overall time that a team of cyclists needs to complete a race. We present an optimisation framework for team pursuit track cycling and show how to evolve strategies using metaheuristics for this interesting real-world problem. Our experimental results show that these heuristics lead to significantly better strategies than state-of-art strategies that are currently used by teams of cyclists.
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Notes
- 1.
It is an extension based on [5] to incorporate drafting benefits.
- 2.
Note that other optimiziation software may outperform CMA-ES, but as its algorithmic setup is virtually parameter-free, no fine-tuning of parameters was required.
- 3.
Based on private communication with the Australian Institute of Sport cycling team.
- 4.
Note that other ways to model fatigue can be incorporated into the fitness function, such as a declining maximum performance if the first rider stays in front for too long.
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Acknowledgements
The authors would like to thank Dr David Martin from the Australian Institute of Sport cycling program and Dr Tammie Ebert from Cycling Australia for their valuable support.
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Wagner, M., Day, J., Jordan, D., Kroeger, T., Neumann, F. (2013). Evolving Pacing Strategies for Team Pursuit Track Cycling. In: Di Gaspero, L., Schaerf, A., Stützle, T. (eds) Advances in Metaheuristics. Operations Research/Computer Science Interfaces Series, vol 53. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6322-1_4
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DOI: https://doi.org/10.1007/978-1-4614-6322-1_4
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