Solving the unit-load pre-marshalling problem in block stacking storage systems with multiple access directions

Block stacking storage systems are highly adaptable warehouse systems with low investment costs. With multiple, deep lanes they can achieve high storage densities, but accessing some unit loads can be time-consuming. The unit-load pre-marshalling problem sorts the unit loads in a block stacking storage system in off-peak time periods to prepare for upcoming orders. The goal is to find a minimum number of unit-load moves needed to sequence a storage bay in ascending order based on the retrieval priority group of each unit load. In this paper, we present two solution approaches for determining the minimum number of unit-load moves. We show that for storage bays with one access direction, it is possible to adapt existing, optimal tree search procedures and lower bound heuristics from the container pre-marshalling problem. For multiple access directions, we develop a novel, two-step solution approach based on a network flow model and an A* algorithm with an adapted lower bound that is applicable in all scenarios. We further analyze the performance of the presented solutions in computational experiments for randomly generated problem instances and show that multiple access directions greatly reduce both the total access time of unit loads and the required sorting effort

Automatic Building of a Repository for Component-based Synthesis of Warehouse Simulation Models

Simulations are a common tool in the warehouse planning and adoption process for evaluating and comparing variants of a storage system. But simulation modeling is a complex and time-consuming task. Due to limited resources, often not all possible system variants can be modeled. A promising solution is the migration of an existing simulation model to enable component-based software synthesis. An inhabitation algorithm composes structural variants according to a synthesis goal given a repository of typed components. In this paper, we automatically generate a repository and synthesize simulation model variants using a block stacking warehouse simulation model as an example

Autonom organisierte Bodenblocklager: Ein Überblick über Entscheidungsprobleme und wesentliche Herausforderungen

In autonomously organized block stacking ware-houses, Automated Guided Vehicles (AGVs) control material handling without requiring any technical in-tegration or Warehouse Management System (WMS). In this paper, we present related decision problems and provide a short literature overview for each one. We found that many existing approaches do not exploit the full potential of available flexibility. By focusing on operational decisions, we introduce the autonomous block stacking warehouse problem (ABSWP) and dis-cuss major challenges which must be tackled by future solution approaches.In autonom organisierten Bodenblocklagern über-nehmen Fahrerlose Transportfahrzeuge (FTF) den Materialtransport und benötigen dabei keine techni-sche Anbindung und Lagerverwaltungssoftware. In diesem Beitrag präsentieren wir relevante Entschei-dungsprobleme und geben für jedes einen kurzen Lite-raturüberblick. Wir stellen dabei fest, dass viele beste-hende Ansätze noch nicht das voll verfügbare Potential an Flexibilität nutzen. Mit der Fokussierung auf opera-tive Entscheidungen, präsentieren wir das Autonomous Block Stacking Warehouse Problem (ABSWP) und diskutieren die größten Herausforderungen, welche durch zukünftige Lösungsansätze zu bewältigen sind