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A Fully Polynomial Time Approximation Scheme for Packing While Traveling

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Algorithmic Aspects of Cloud Computing (ALGOCLOUD 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11409))

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Abstract

Understanding the interaction between different combinatorial optimization problems is a challenging task of high relevance for numerous real-world applications including modern computer and memory architectures as well as high performance computing. Recently, the Traveling Thief Problem (TTP), as a combination of the classical traveling salesperson problem and the knapsack problem, has been introduced to study these interactions in a systematic way. We investigate the underlying non-linear Packing While Traveling Problem (PWTP) of the TTP where items have to be selected along a fixed route. We give an exact dynamic programming approach for this problem and a fully polynomial time approximation scheme (FPTAS) when maximizing the benefit that can be gained over the baseline travel cost. Our experimental investigations show that our new approaches outperform current state-of-the-art approaches on a wide range of benchmark instances.

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Notes

  1. 1.

    Alternatively, an intermediate city with no item might be deleted from the sequence.

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Acknowledgements

The first, second, and fifth author were supported by Australian Research Council grants DP130104395 and DP140103400. The third author is supported by the Einstein Foundation Berlin in the framework of Matheon.

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Correspondence to Frank Neumann .

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Neumann, F., Polyakovskiy, S., Skutella, M., Stougie, L., Wu, J. (2019). A Fully Polynomial Time Approximation Scheme for Packing While Traveling. In: Disser, Y., Verykios, V. (eds) Algorithmic Aspects of Cloud Computing. ALGOCLOUD 2018. Lecture Notes in Computer Science(), vol 11409. Springer, Cham. https://doi.org/10.1007/978-3-030-19759-9_5

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  • DOI: https://doi.org/10.1007/978-3-030-19759-9_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19758-2

  • Online ISBN: 978-3-030-19759-9

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