The Dynamic Travelling Thief Problem: Benchmarks and Performance of Evolutionary Algorithms
April 25, 2020 ยท Declared Dead ยท ๐ International Conference on Neural Information Processing
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Authors
Ragav Sachdeva, Frank Neumann, Markus Wagner
arXiv ID
2004.12045
Category
cs.NE: Neural & Evolutionary
Citations
9
Venue
International Conference on Neural Information Processing
Last Checked
3 months ago
Abstract
Many real-world optimisation problems involve dynamic and stochastic components. While problems with multiple interacting components are omnipresent in inherently dynamic domains like supply-chain optimisation and logistics, most research on dynamic problems focuses on single-component problems. With this article, we define a number of scenarios based on the Travelling Thief Problem to enable research on the effect of dynamic changes to sub-components. Our investigations of 72 scenarios and seven algorithms show that -- depending on the instance, the magnitude of the change, and the algorithms in the portfolio -- it is preferable to either restart the optimisation from scratch or to continue with the previously valid solutions.
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