Scientific publications

The warehouse system sales process leads from a specific customer request to a specific customer quotation. This process of configuring a warehouse system with existing components involves a sequence of steps which contain increasingly more details. In this chapter, it is shown by two examples that easy-to-use essential system simulation models can be applied early in the sales process with a good cost/benefit ratio.

In recent years, autonomous mobile robots (AMR) have emerged as a means of transportation system in warehouses. The complexity of the transport tasks requires efficient high-level control, i.e. planning and scheduling of the tasks as well as low-level motion control of the robots. Hence, an efficient coordination between robots is needed to achieve flexibility, robustness and scalability of the transportationsystem.

Warehouse management and control systems are responsible for the operations in a warehouse. These systems are usually very complex due to the delivery requirements of the warehouse customers. These delivery requirements are often very specific for a group of customers, which makes it hard to reuse warehouse management and control functionality for other warehouses.

This paper proposes a modeling approach to capture the mapping of an application on a platform. The approach is based on Scenario-Aware Dataflow (SADF) models. In contrast to the related work, we express the complete design-space in a single formal SADF model. This allows us to have a compact and explorable state-space linked with an executable model capable of symbolically analyzing different mappings for their timing behavior.

Wireless Sensor Networks (WSNs) are commonly deployed in dynamic environments where events, such as moving sensor nodes and changing external interference, impact the performance, or Quality-of-Service (QoS), of the network. QoS is expressed by the values of multiple, possibly conflicting, network quality metrics, such as network lifetime and maximum latency of communicating a packet to the sink.

Constructing a model of a system for model-based testing, simulation, or model checking can be cumbersome for existing, third party, or legacy components. Active automata learning, a form of black-box reverse engineering, and in particular Angluin’s L⋆ algorithm, support the automatic inference of a model from a System Under Learning (SUL), through observations and tests.

Wireless Sensor Networks (WSNs) are commonly deployed in dynamic environments where events, such as moving sensor nodes and changing external interference, impact the performance, or Quality-of-Service (QoS), of the network. QoS is expressed by the values of multiple, possibly conflicting, network quality metrics, such as network lifetime and maximum latency of communicating a packet to the sink.

This thesis addresses the Flexible Job Shop Scheduling Problem (FJSP) with three extensions: Sequence-Dependent Setup Times (SDST), Blocking tasks and Alternative Process Plans (APPs). The research evaluates the efficacy of two distinct optimization paradigms: Constraint Programming (CP) and Multivalued Decision Diagrams (MDDs).

To assess the practical performance of a system, one needs to consider the system in its operating environment. This report presents an approach for analysing and optimising the performance of High-Mix Low-Volume (HMLV) automated production lines. The approach comprises three methods: (1) a method to specify a production line’s equipment, workload and allocation, (2) a method based on constraint graphs to compute the latency of a specified allocation, and (3) a method based on constraint programming to find the optimal allocation of a production line’s workload on its equipment.

Variability and evolution are key drivers of complexity in high-tech equipment. Every product has many variation points, resulting in a large number of unique system configurations. These systems must be maintained throughout their life-time, which may last several decades. During this time, digital technologies, e.