TY - GEN A1 - Maristany de las Casas, Pedro A1 - Borndörfer, Ralf A1 - Kraus, Luitgard A1 - Sedeño-Noda, Antonio T1 - An FPTAS for Dynamic Multiobjective Shortest Path Problems N2 - We propose in this paper the Dynamic Multiobjective Shortest Problem. It features multidimensional states that can depend on several variables and not only on time; this setting is motivated by flight planning and electric vehicle routing applications. We give an exact algorithm for the FIFO case and derive from it an FPTAS, which is computationally efficient. It also features the best known complexity in the static case. T3 - ZIB-Report - 20-31 KW - Multiobjective Shortest Paths KW - Time Dependent Shortest Paths KW - Multiobjective Approximation Algorithms KW - Flight Planning Problem Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-80954 ER - TY - JOUR A1 - Maristany de las Casas, Pedro A1 - Borndörfer, Ralf A1 - Kraus, Luitgard A1 - Sedeño-Noda, Antonio T1 - An FPTAS for Dynamic Multiobjective Shortest Path Problems JF - Algorithms N2 - The Dynamic Multiobjective Shortest Path problem features multidimensional costs that can depend on several variables and not only on time; this setting is motivated by flight planning applications and the routing of electric vehicles. We give an exact algorithm for the FIFO case and derive from it an FPTAS for both, the static Multiobjective Shortest Path (MOSP) problems and, under mild assumptions, for the dynamic problem variant. The resulting FPTAS is computationally efficient and beats the known complexity bounds of other FPTAS for MOSP problems. Y1 - 2021 U6 - https://doi.org/https://doi.org/10.3390/a14020043 VL - 14 IS - 2 SP - 1 EP - 22 ER - TY - THES A1 - Kraus, Luitgard T1 - A Label Setting Multiobjective Shortest Path FPTAS N2 - Algorithms that solve the shortest path problem can largely be split into the two categories of label setting and label correcting. The Multiobjective Shortest Path (MOSP) problem is a generalization of the classical shortest path problem in terms of the dimension of the cost function. We explore the differences of two similar MOSP label setting algorithms. Furthermore, we present and prove a general method of how to derive Fully Polynomial Time Approximation Schemes (FPTAS) for MOSP label setting algorithms. Finally, we explore two pruning techniques for the one to one variants of exact label setting MOSP algorithms and adapt them to their FPTAS variants. Y1 - 2021 ER - TY - JOUR A1 - Maristany de las Casas, Pedro A1 - Kraus, Luitgard A1 - Sedeno-Noda, Antonio A1 - Borndörfer, Ralf T1 - Targeted multiobjective Dijkstra Algorithm JF - Networks N2 - We introduce the Targeted Multiobjective Dijkstra Algorithm (T-MDA), a label setting algorithm for the One-to-One Multiobjective Shortest Path (MOSP) Problem. It is based on the recently published Multiobjective Dijkstra Algorithm (MDA) and equips it with A*-like techniques. For any explored subpath, a label setting MOSP algorithm decides whether the subpath can be discarded or must be stored as part of the output. A major design choice is how to store subpaths from the moment they are first explored until the mentioned final decision can be made. The T-MDA combines the polynomially bounded size of the priority queue used in the MDA and alazy management of paths that are not in the queue. The running time bounds from the MDA remain valid. In practice, the T-MDA outperforms known algorithms from the literature and the increased memory consumption is negligible. In this paper, we benchmark the T-MDA against an improved version of the state of the art NAMOA∗drOne-to-One MOSP algorithm from the literature on a standard testbed. Y1 - 2023 U6 - https://doi.org/10.1002/net.22174 VL - 82 IS - 3 SP - 277 EP - 298 ER -