Abstract
In this paper, we are interested in a recent variant of the Traveling Salesman Problem (TSP) in which the Knapsack Problem (KP) is integrated. In the literature, this problem is called Traveling Thief Problem (TTP). Interested by the inherent computational challenge of the new problem, we investigate a hybrid evolutionary approach for solving the TTP. In order to evaluate the efficiency of the proposed approach, we carried out some numerical experiments on benchmark instances. The results show the efficiency of the introduced method in solving medium sized instances. In particular, the algorithm improves some best known solutions of the literature. In the case of large instances, our approach gives competitive results that need to be improved in order to obtain better results.
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Notes
- 1.
TSP Test Data, see comopt.ifi.uni-heidelberg.de/software/TSPLIB95/index.html.
- 2.
Wagner et al. have done their computational experiments on an Xeon 2.66 GHz quad core CPU and ran each algorithm for 10 min [21].
- 3.
Solutions available at comopt.ifi.uni-heidelberg.de/software/TSPLIB95/STSP.html.
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Moeini, M., Schermer, D., Wendt, O. (2017). A Hybrid Evolutionary Approach for Solving the Traveling Thief Problem. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10405. Springer, Cham. https://doi.org/10.1007/978-3-319-62395-5_45
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