10 research outputs found
A fully polynomial time approximation scheme for packing while traveling
Understanding the interactions between different combinatorial optimisation
problems in real-world applications is a challenging task. 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 (PWT) problem 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
maximising 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
A Fully Polynomial Time Approximation Scheme for Packing While Traveling
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
A Fully Polynomial Time Approximation Scheme for Packing While Traveling
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.Frank Neumann, Sergey Polyakovskiy, Martin Skutella, Leen Stougie, and Junhua W
A Fully Polynomial Time Approximation Scheme for Packing While Traveling
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.Frank Neumann, Sergey Polyakovskiy, Martin Skutella, Leen Stougie, and Junhua W
A Fully Polynomial Time Approximation Scheme for Packing While Traveling
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