Coordinated Lot-sizing and Dynamic Prizing under a Supplier All-units Quantity Discount

We consider an economic order quantity model where the supplier offers an all-units quantity discount and a price sensitive customer demand. We compare a decentralized decision framework where selling price and replenishment policy are determined independently to simultaneous decision making. Constant and dynamic pricing are distinguished. We derive structural properties and develop algorithms that determine the optimal pricing and replenishment policy and show how quantity discounts not only influence the purchasing strategy but also the pricing policy. A sensitivity analysis indicates the impact of the fixed-holding cost ratio, the discount policy, and the customers' price sensitivity on the optimal decisions.

Dynamic merge of discrete goods flow – Impact on throughput and efficiency

Continuous conveyors with a dynamic merge were developed with adaptable control equipment to differentiate these merges from competing Stop-and-Go merges. With a dynamic merge, the partial flows are manipulated by influencing speeds so that transport units need not stop for the merge. This leads to a more uniform flow of materials, which is qualitatively observable and verifiable in long-term measurements. And although this type of merge is visually mesmerizing, does it lead to advantages from the view of material flow technology? Our study with real data indicates that a dynamic merge shows a 24% increase in performance, but only for symmetric or nearly symmetric flows. This performance advantage decreases as the flows become less symmetric, approaching the throughput of traditional Stop-and-Go merges. And with a cost premium for a continuous merge of approximately 10% due to the additional technical components (belt conveyor, adjustable drive engines, software, etc.), this restricts their economical use.

Bitmap Movement Detection: HDR for Dynamic Scenes

Exposure Fusion and other HDR techniques generate well-exposed images from a bracketed image sequence while reproducing a large dynamic range that far exceeds the dynamic range of a single exposure. Common to all these techniques is the problem that the smallest movements in the captured images generate artefacts (ghosting) that dramatically affect the quality of the final images. This limits the use of HDR and Exposure Fusion techniques because common scenes of interest are usually dynamic. We present a method that adapts Exposure Fusion, as well as standard HDR techniques, to allow for dynamic scene without introducing artefacts. Our method detects clusters of moving pixels within a bracketed exposure sequence with simple binary operations. We show that the proposed technique is able to deal with a large amount of movement in the scene and different movement configurations. The result is a ghost-free and highly detailed exposure fused image at a low computational cost.