  In this article, a benchmark for real-world bin packing problems is proposed.
This dataset consists of 12 instances of varying levels of complexity regarding
size (with the number of packages ranging from 38 to 53) and user-defined
requirements. In fact, several real-world-oriented restrictions were taken into
account to build these instances: i) item and bin dimensions, ii) weight
restrictions, iii) affinities among package categories iv) preferences for
package ordering and v) load balancing. Besides the data, we also offer an own
developed Python script for the dataset generation, coined Q4RealBPP-DataGen.
The benchmark was initially proposed to evaluate the performance of quantum
solvers. Therefore, the characteristics of this set of instances were designed
according to the current limitations of quantum devices. Additionally, the
dataset generator is included to allow the construction of general-purpose
benchmarks. The data introduced in this article provides a baseline that will
encourage quantum computing researchers to work on real-world bin packing
problems.
