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.

Additional Metadata
Persistent URL dx.doi.org/10.1007/978-3-030-19759-9_5
Series Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence
Citation
Neumann, F, Polyakovskiy, S, Skutella, M, Stougie, L, & Wu, J. (2019). A Fully Polynomial Time Approximation Scheme for Packing While Traveling. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence. doi:10.1007/978-3-030-19759-9_5