Abstract
A common problem when applying heuristics is that they often perform well on some problem instances, but poorly on others. We work towards developing a hyper-heuristic that manages delivery of good quality solutions to Vehicle Routing Problem instances with only limited prior knowledge of the problem domain to be solved. This paper develops a hyper-heuristic, using Grammatical Evolution, to generate and apply heuristics that develop good solutions. Through a series of experiments we expand and refine the technique, achieving good quality results on 40 well known Capacitated Vehicle Routing Problem instances.
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Marshall, R.J., Johnston, M., Zhang, M. (2014). Developing a Hyper-Heuristic Using Grammatical Evolution and the Capacitated Vehicle Routing Problem. In: Dick, G., et al. Simulated Evolution and Learning. SEAL 2014. Lecture Notes in Computer Science, vol 8886. Springer, Cham. https://doi.org/10.1007/978-3-319-13563-2_56
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DOI: https://doi.org/10.1007/978-3-319-13563-2_56
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