The dataset contains a collection of experiment results and event logs generated. The experiments comprise a logistics case study involving the transport of products that are subject to quality depreciation. The products are transported on smart pallets, which enables us to keep track of various measures (e.g., location, quality depreciation level, etc.). We considered the problem as a special case of the dynamic pickup and delivery problem in which objects need to be transported between an origin and a destination. The case study is implemented in a discrete-event simulation model. This dataset contains the experiment input (i.e., input parameters) and results (i.e., simulation output files and filtered output files considering the removal of a warm-up period). As output, we also provide event logs, which could, for example, be used for model verification or process mining purposes.