@inproceedings{EulerBorndoerfer, author = {Euler, Ricardo and Bornd{\"o}rfer, Ralf}, title = {A Graph- and Monoid-based Framework for Price-Sensitive Routing in Local Public Transportation Networks}, series = {19th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2019)}, volume = {75}, booktitle = {19th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2019)}, doi = {10.4230/OASIcs.ATMOS.2019.12}, pages = {12:1 -- 12:15}, abstract = {We present a novel framework to mathematically describe the fare systems of local public transit companies. The model allows the computation of a provably cheapest itinerary even if prices depend on a number of parameters and non-linear conditions. Our approach is based on a ticket graph model to represent tickets and their relation to each other. Transitions between tickets are modeled via transition functions over partially ordered monoids and a set of symbols representing special properties of fares (e.g. surcharges). Shortest path algorithms rely on the subpath optimality property. This property is usually lost when dealing with complicated fare systems. We restore it by relaxing domination rules for tickets depending on the structure of the ticket graph. An exemplary model for the fare system of Mitteldeutsche Verkehrsbetriebe (MDV) is provided. By integrating our framework in the multi-criteria RAPTOR algorithm we provide a price-sensitive algorithm for the earliest arrival problem and assess its performance on data obtained from MDV. We discuss three preprocessing techniques that improve run times enough to make the algorithm applicable for real-time queries.}, language = {en} } @inproceedings{EulerBorndoerferStrunketal., author = {Euler, Ricardo and Bornd{\"o}rfer, Ralf and Strunk, Timo and Takkula, Tuomo}, title = {ULD Build-Up Scheduling with Dynamic Batching in an Air Freight Hub}, series = {Operations Research Proceedings 2021}, booktitle = {Operations Research Proceedings 2021}, doi = {10.1007/978-3-031-08623-6_38}, pages = {254 -- 260}, abstract = {Air freight is usually shipped in standardized unit load devices (ULDs). The planning process for the consolidation of transit cargo from inbound flights or locally emerging shipments into ULDs for outbound flights is called build-up scheduling. More specifically, outbound ULDs must be assigned a time and a workstation subject to both workstation capacity constraints and the availability of shipments which in turn depends on break-down decisions for incoming ULDs. ULDs scheduled for the same outbound flight should be built up in temporal and spatial proximity. This serves both to minimize overhead in transportation times and to allow workers to move freight between ULDs. We propose to address this requirement by processing ULDs for the same outbound flight in batches. For the above build-up scheduling problem, we introduce a multi-commodity network design model. Outbound flights are modeled as commodities; transit cargo is represented by cargo flow volume and unpack and batch decisions are represented as design variables. The model is solved with a standard MIP solver on a set of benchmark data. For instances with a limited number of resource conflicts, near-optimal solutions are found in under two hours for a whole week of operations.}, language = {en} } @inproceedings{EulerBorndoerferPuchertetal., author = {Euler, Ricardo and Bornd{\"o}rfer, Ralf and Puchert, Christian and Takkula, Tuomo}, title = {ULD Build-Up Scheduling with Logic-Based Benders Decomposition}, series = {Integration of Constraint Programming, Artificial Intelligence, and Operations Research}, volume = {14742}, booktitle = {Integration of Constraint Programming, Artificial Intelligence, and Operations Research}, doi = {https://doi.org/10.1007/978-3-031-60597-0_17}, pages = {259 -- 276}, abstract = {We study a complex planning and scheduling problem arising from the build-up process of air cargo pallets and containers, collectively referred to as unit load devices (ULD), in which ULDs must be assigned to workstations for loading. Since air freight usually becomes available gradually along the planning horizon, ULD build-ups must be scheduled neither too early to avoid underutilizing ULD capacity, nor too late to avoid resource conflicts with other flights. Whenever possible, ULDs should be built up in batches, thereby giving ground handlers more freedom to rearrange cargo and utilize the ULD's capacity efficiently. The resulting scheduling problem has an intricate cost function and produces large time-expanded models, especially for longer planning horizons. We propose a logic-based Benders decomposition approach that assigns batches to time intervals and workstations in the master problem, while the actual schedule is decided in a subproblem. By choosing appropriate intervals, the subproblem becomes a feasibility problem that decomposes over the workstations. Additionally, the similarity of many batches is exploited by a strengthening procedure for no-good cuts. We benchmark our approach against a time-expanded MIP formulation from the literature on a publicly available data set. It solves 15\% more instances to optimality and decreases run times by more than 50\% in the geometric mean. This improvement is especially pronounced for longer planning horizons of up to one week, where the Benders approach solves over 50\% instances more than the baseline}, language = {en} }